diff --git a/CHANGELOG.md b/CHANGELOG.md
index 9fd09cdc..94943ebc 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -22,8 +22,10 @@ the frozen-backend fallback mirror it for their toolchains.
 
 ### Docs
 - The READMEs now lead with download buttons and a three-step first-clone walkthrough, and a new benchmarks page anchors measured per-engine/per-device numbers on the in-repo harness (#1555)
+- Every engine now has its own guide — 21 new pages under docs/engines plus an index covering all 16 TTS and 11 ASR engines, linked from both READMEs (#1556)
 
 ### Fixed
+- The crash-isolated ASR sidecar and its download preflight now agree on which model to load — setting the shared faster-whisper model variable applies to both variants instead of the sidecar quietly using a different one (#1556)
 - "Ready" now requires the deep health probe (a working database-backed route), not just the identity probe — a backend whose install broke underneath can no longer be announced up while every real request fails (#1548)
 - Supervisor restarts after repeat crashes now back off (immediate, then 5s, then 15s) instead of respawning back-to-back, so a tight crash loop can't burn the whole restart budget in seconds (#1548)
 
diff --git a/README.md b/README.md
index 797222ab..adf39184 100644
--- a/README.md
+++ b/README.md
@@ -218,7 +218,7 @@ Professional-grade voice AI, minus the subscription and the cloud. Convinced? [C
 
 ### 🗣️ TTS Engines
 
-**16 engines, one picker.** VoiceStudio (default, 600+ languages) is always available; seven more are opt-in and auto-detected (CosyVoice 3, GPT-SoVITS, VoxCPM2, MOSS-TTS-Nano, KittenTTS, MLX-Audio, Sherpa-ONNX), plus eight lazy-installed opt-ins (IndexTTS 2.5, OmniVoice GGUF, OmniVoice subprocess, PocketTTS, Supertonic 3, MOSS-TTS-v1.5, dots.tts, Confucius4-TTS). Switch in **Model Catalogue → Engines** — or from anywhere with <kbd>Ctrl</kbd>/<kbd>Cmd</kbd>+<kbd>E</kbd>; the choice applies everywhere synthesis happens.
+**16 engines, one picker.** VoiceStudio (default, 600+ languages) is always available; seven more are opt-in and auto-detected (CosyVoice 3, GPT-SoVITS, VoxCPM2, MOSS-TTS-Nano, KittenTTS, MLX-Audio, Sherpa-ONNX), plus eight lazy-installed opt-ins (IndexTTS 2.5, OmniVoice GGUF, OmniVoice subprocess, PocketTTS, Supertonic 3, MOSS-TTS-v1.5, dots.tts, Confucius4-TTS). Switch in **Model Catalogue → Engines** — or from anywhere with <kbd>Ctrl</kbd>/<kbd>Cmd</kbd>+<kbd>E</kbd>; the choice applies everywhere synthesis happens. **Every engine has its own guide: [docs/engines](docs/engines/README.md).**
 
 <details>
 <summary><b>📊 The full matrix</b> — 16 engines × platform × clone/instruct × license</summary>
@@ -228,15 +228,15 @@ Professional-grade voice AI, minus the subscription and the cloud. Convinced? [C
 | Engine | Languages | Clone | Instruct | Linux | macOS ARM | Windows | License |
 |--------|:---------:|:-----:|:--------:|:-----:|:---------:|:-------:|:-------:|
 | **VoiceStudio** (default, powered by k2-fsa/OmniVoice) | 600+ | ✅ | ✅ | ✅ CUDA/CPU | ✅ MPS | ✅ CUDA/CPU | Built-in |
-| **CosyVoice 3** | 9 + 18 dialects | ✅ | ✅ | ✅ CUDA/CPU | ✅ MPS | ✅ CUDA/CPU | Apache-2.0 |
+| **CosyVoice 3** | 9 + 18 dialects | ✅ | ✅ | ✅ CUDA/CPU | ✅ CPU | ✅ CUDA/CPU | Apache-2.0 |
 | **GPT-SoVITS** | 5 | ✅ | — | ✅ CUDA/CPU | — | ✅ CUDA/CPU | MIT |
 | **VoxCPM2** | 30 | ✅ | ✅ | ✅ CUDA/CPU | ✅ MPS | ✅ CUDA/CPU | Apache-2.0 |
 | **MOSS-TTS-Nano** | 20 | ✅ | — | ✅ CUDA/CPU | ✅ CPU | ✅ CUDA/CPU | Apache-2.0 |
 | **KittenTTS** | English | — | — | ✅ CPU | ✅ CPU | ✅ CPU | MIT |
 | **MLX-Audio** (Kokoro, Qwen3-TTS, CSM, Dia, …) | Multi | Varies | Varies | ❌ | ✅ Native | ❌ | Varies |
 | **Sherpa-ONNX** | 20+ | — | — | ✅ CUDA/CPU | ✅ CPU | ✅ CUDA/CPU | Apache-2.0 |
-| **IndexTTS 2.5** ⚡ | ZH · EN · JA · ES · AR | ✅ | — | ✅ CUDA | — | ✅ CUDA | Bilibili model license¹ |
-| **OmniVoice GGUF** ⚡ | 600+ | ✅ | ✅ | ✅ CPU | ✅ CPU | ✅ CPU | Built-in |
+| **IndexTTS 2.5** ⚡ | ZH · EN · JA · ES · AR | ✅ | — | ✅ CUDA/CPU | ✅ CPU | ✅ CUDA/CPU | Bilibili model license¹ |
+| **OmniVoice GGUF** ⚡ | 600+ | ✅ | ✅ | ✅ CUDA/CPU | ✅ MPS/CPU | ✅ CUDA/CPU | Built-in |
 | **OmniVoice (subprocess)** ⚡² | 600+ | ✅ | ✅ | ✅ CUDA/CPU | ✅ MPS | ✅ CUDA/CPU | Built-in |
 | **PocketTTS** ⚡ (Kyutai) | EN · FR · DE · PT · IT · ES | ✅ | — | ✅ CPU | ✅ CPU | ✅ CPU | CC-BY-4.0 (gated)³ |
 | **Supertonic 3** ⚡ | 31 | — | — | ✅ CPU | ✅ CPU | ✅ CPU | OpenRAIL-M |
@@ -275,7 +275,7 @@ another machine, set `OMNIVOICE_GPTSOVITS_URL` to its credential-free
 
 ### 🎧 ASR Engines
 
-**11 engines** — they power dictation, video dubbing, and subtitles. **WhisperX** is the cross-platform default (~100 languages, word-level timing); the rest are opt-in and auto-detected. Switch in **Model Catalogue → Engines**. Ten run fully on-device; the eleventh (OpenAI-compatible) is an optional remote client for Qwen3-ASR or any compatible server.
+**11 engines** — they power dictation, video dubbing, and subtitles. **WhisperX** is the cross-platform default (~100 languages, word-level timing); the rest are opt-in and auto-detected. Switch in **Model Catalogue → Engines**. Ten run fully on-device; the eleventh (OpenAI-compatible) is an optional remote client for Qwen3-ASR or any compatible server. **Per-engine guides: [docs/engines](docs/engines/README.md).**
 
 <details>
 <summary><b>📊 The full lineup</b> — 11 engines, what each is best at, and compute-type notes</summary>
diff --git a/README_CN.md b/README_CN.md
index e62d187a..58b833d9 100644
--- a/README_CN.md
+++ b/README_CN.md
@@ -180,8 +180,8 @@ Hugging Face Token 的配置见
 | **API 密钥** | 需要账号 | 本地流程不需要 |
 | **GPU 支持** | 不适用（云端） | CUDA · Apple Silicon · ROCm（Linux）· CPU |
 | **桌面应用** | ❌ | ✅ macOS · Windows · Linux |
-| **TTS 引擎** | 1 | **14** — [完整矩阵](#tts-engines) |
-| **ASR 引擎** | 1 | **10** — [完整阵容](#asr-engines) |
+| **TTS 引擎** | 1 | **16** — [完整矩阵](#tts-engines) |
+| **ASR 引擎** | 1 | **11** — [完整阵容](#asr-engines) |
 | **MCP 服务器** | ❌ | ✅ 可从 Claude、Cursor 及任何 MCP 客户端使用 |
 | **自检** | ❌ | ✅ 诊断套件、错误日志、脱敏调试包 |
 | **可定制** | ❌ 闭源 | ✅ 随你 Fork、扩展、发布 |
@@ -221,10 +221,10 @@ Hugging Face Token 的配置见
 
 ### 🗣️ TTS 引擎
 
-**14 个引擎，一个选择器。** VoiceStudio（默认，支持 600+ 语言）始终可用；另有七个引擎可选装并自动检测（CosyVoice 3、GPT-SoVITS、VoxCPM2、MOSS-TTS-Nano、KittenTTS、MLX-Audio、Sherpa-ONNX），外加六个按需延迟安装的重量级引擎（IndexTTS 2.5、OmniVoice GGUF、Supertonic 3、MOSS-TTS-v1.5、dots.tts、Confucius4-TTS）。在 **设置 → TTS 引擎** 中切换；所选引擎将应用于所有语音合成场景。
+**16 个引擎，一个选择器。** VoiceStudio（默认，支持 600+ 语言）始终可用；另有七个引擎可选装并自动检测（CosyVoice 3、GPT-SoVITS、VoxCPM2、MOSS-TTS-Nano、KittenTTS、MLX-Audio、Sherpa-ONNX），外加八个按需延迟安装的引擎（IndexTTS 2.5、OmniVoice GGUF、OmniVoice 子进程版、PocketTTS、Supertonic 3、MOSS-TTS-v1.5、dots.tts、Confucius4-TTS）。在 **设置 → TTS 引擎** 中切换；所选引擎将应用于所有语音合成场景。**每个引擎都有独立指南：[docs/engines](docs/engines/README.md)（英文）。**
 
 <details>
-<summary><b>📊 完整矩阵</b>——14 个引擎 × 平台 × 克隆/指令 × 许可证</summary>
+<summary><b>📊 完整矩阵</b>——16 个引擎 × 平台 × 克隆/指令 × 许可证</summary>
 
 <br/>
 
@@ -261,10 +261,10 @@ Hugging Face Token 的配置见
 
 ### 🎧 ASR 引擎
 
-**10 个引擎**——它们驱动听写、视频配音和字幕。**WhisperX** 是跨平台的默认引擎（约 100 种语言，词级时间对齐）；其余引擎均为可选装并自动检测。在 **设置 → 引擎** 中切换。九个完全在本地设备上运行；第十个（OpenAI 兼容）是可选的远程客户端，可用于 Qwen3-ASR 或任何兼容的服务器。
+**11 个引擎**——它们驱动听写、视频配音和字幕。**WhisperX** 是跨平台的默认引擎（约 100 种语言，词级时间对齐）；其余引擎均为可选装并自动检测。在 **设置 → 引擎** 中切换。十个完全在本地设备上运行；第十一个（OpenAI 兼容）是可选的远程客户端，可用于 Qwen3-ASR 或任何兼容的服务器。
 
 <details>
-<summary><b>📊 完整阵容</b>——10 个引擎、各自的强项与计算类型说明</summary>
+<summary><b>📊 完整阵容</b>——11 个引擎、各自的强项与计算类型说明</summary>
 
 <br/>
 
@@ -281,7 +281,7 @@ Hugging Face Token 的配置见
 | **sherpa-onnx**（实时听写） | `sherpa-onnx-asr` | 25 种欧洲语言 + 90+ | 实时、快于实时的听写——小体积流式/离线 ONNX 模型（Parakeet TDT v3/v2、流式 Zipformer 与 Paraformer、Whisper Tiny），CPU 运行，macOS / Windows / Linux 表现完全一致。在 **设置 → 语音** 中按模型选择。 |
 | **OpenAI 兼容** ⚠️ 远程 | `openai-compat-asr` | 取决于服务器 | 当下通往 **Qwen3-ASR** 的路径（自托管服务器，无需等 transformers 支持）、任何 OpenAI 兼容的转录端点，或 OpenAI 官方 API——无需安装，在 **设置 → 引擎**（ASR 标签页）中配置并测试连接。音频会离开你的设备，发送到你指定的任何服务器；参见 [docs/engines/openai-compatible-asr.md](docs/engines/openai-compatible-asr.md)。 |
 
-> Whisper 系列引擎覆盖约 100 种语言；**FunASR / SenseVoice** 额外提供一条多语言一体化路径，内置语音活动检测与行内说话人分离。**sherpa-onnx** 驱动实时听写的模型选择器——你边说，文字边出现。每个引擎都在本地设备上运行——无需 API 密钥，无需云端。
+> Whisper 系列引擎覆盖约 100 种语言；**FunASR / SenseVoice** 额外提供一条多语言一体化路径，内置语音活动检测与行内说话人分离。**sherpa-onnx** 驱动实时听写的模型选择器——你边说，文字边出现。除可选的 OpenAI 兼容远程客户端外，所有引擎都在本地设备上运行——无需 API 密钥，无需云端。
 
 > **GPU 不支持高效 float16？** 在较老的 NVIDIA GPU（Maxwell/Pascal、GTX 16xx）上，或在 CTranslate2/cuDNN 版本不匹配之后，CTranslate2 系 ASR 引擎（WhisperX、Faster-Whisper）无法运行 `float16`，VoiceStudio 会自动改用 `int8` 重试——无需配置。如果转录仍然失败，可用 `ASR_COMPUTE_TYPE` 环境变量固定计算类型（逃生舱口）：`ASR_COMPUTE_TYPE=int8`（CPU 用 `float32`）。将其设为 `int8` 并重启后端。
 
diff --git a/backend/engines/_asr_sidecar/main.py b/backend/engines/_asr_sidecar/main.py
index db6ebf7a..d0c04c58 100644
--- a/backend/engines/_asr_sidecar/main.py
+++ b/backend/engines/_asr_sidecar/main.py
@@ -85,7 +85,16 @@ def _get_model():
     global _model
     if _model is None:
         from faster_whisper import WhisperModel
-        name = os.environ.get("ASR_MODEL_FW", "large-v3")
+        # Same weights as in-process faster-whisper: ASR_MODEL_FASTER selects
+        # for BOTH variants, ASR_MODEL_FW stays as a sidecar-only override.
+        # Before this, the sidecar read only ASR_MODEL_FW while the download
+        # preflight read ASR_MODEL_FASTER — set one and the other variant (or
+        # the preflight) quietly used a different model.
+        name = (
+            os.environ.get("ASR_MODEL_FW")
+            or os.environ.get("ASR_MODEL_FASTER")
+            or "large-v3"
+        )
         try:
             import torch
             device = "cuda" if torch.cuda.is_available() else "cpu"
diff --git a/backend/services/asr_backend.py b/backend/services/asr_backend.py
index 4e317ddc..8afafbdf 100644
--- a/backend/services/asr_backend.py
+++ b/backend/services/asr_backend.py
@@ -2325,7 +2325,7 @@ _INSTALL_HINTS: dict[str, str] = {
         "mac-ARM source installs since 0.3.22. Parakeet TDT v3 on the GPU via "
         "MLX: 25 European languages, word timestamps, ~2 GB unified memory.)"
     ),
-    "moonshine":       "pip install useful-moonshine  (edge/CPU-optimized ASR)",
+    "moonshine":       "uv pip install moonshine-onnx  (or moonshine-voice; edge/CPU-optimized ASR)",
     "funasr":          "pip install funasr  (SenseVoiceSmall + FSMN-VAD; CUDA or CPU)",
     "sherpa-onnx-asr": "uv add sherpa-onnx  (ONNX live dictation; CPU, cross-platform)",
     "openai-compat-asr": (
@@ -3120,10 +3120,18 @@ def _offline_asr_repo(backend_id: str | None = None) -> str | None:
     bid = backend_id or active_backend_id()
     if bid == "whisperx":
         return _fw_repo(os.environ.get("ASR_MODEL_WHISPERX", "large-v3"))
-    if bid in ("faster-whisper", "faster-whisper-isolated"):
-        # The crash-isolated sidecar loads the SAME CT2 weights as in-process
-        # faster-whisper (it reuses the ASR_MODEL_FASTER selection).
+    if bid == "faster-whisper":
         return _fw_repo(os.environ.get("ASR_MODEL_FASTER", _FASTER_WHISPER_DEFAULT))
+    if bid == "faster-whisper-isolated":
+        # Mirror the sidecar's own resolution (_asr_sidecar/main.py):
+        # ASR_MODEL_FW is a sidecar-only override, otherwise the shared
+        # ASR_MODEL_FASTER selection applies — so the preflight can never
+        # download a different repo than the sidecar will load.
+        return _fw_repo(
+            os.environ.get("ASR_MODEL_FW")
+            or os.environ.get("ASR_MODEL_FASTER")
+            or _FASTER_WHISPER_DEFAULT
+        )
     if bid == "mlx-whisper":
         return os.environ.get("ASR_MODEL", _MLX_MODEL_DEFAULT)
     if bid == "parakeet-mlx":
diff --git a/backend/services/tts_backend.py b/backend/services/tts_backend.py
index 75486c5d..f50418aa 100644
--- a/backend/services/tts_backend.py
+++ b/backend/services/tts_backend.py
@@ -1092,7 +1092,8 @@ class KittenTTSBackend(TTSBackend):
       - English only
       - Much faster + much smaller install
 
-    Preset voice is chosen via `extras["voice"]` (defaults to "Jasper"). Any
+    Preset voice is chosen via `extras["voice"]` (defaults to DEFAULT_VOICE,
+    "expr-voice-2-f"). Any
     `ref_audio` / `instruct` / `language` arg is ignored with a log line so
     the common call-site doesn't need to know which engine it's talking to.
     """
diff --git a/docs/engines/README.md b/docs/engines/README.md
new file mode 100644
index 00000000..534d6891
--- /dev/null
+++ b/docs/engines/README.md
@@ -0,0 +1,57 @@
+# Engine guides
+
+One page per engine: what it's for, what it needs, how to enable it, and its
+quirks. Select engines in **Model Catalogue → Engines** (or quick-switch with
+<kbd>Ctrl</kbd>/<kbd>Cmd</kbd>+<kbd>E</kbd>), or pin one with
+`OMNIVOICE_TTS_BACKEND` / `OMNIVOICE_ASR_BACKEND`.
+
+Measured speed/VRAM numbers live in [benchmarks](../benchmarks.md); what each
+engine can do expressively in [expressive-speech](../expressive-speech.md);
+sidecar disk footprints in [disk-usage](disk-usage.md); the bar a new engine
+must clear in [engine-acceptance](../engine-acceptance.md).
+
+New to VoiceStudio? Install the app first — [macOS](../install/macos.md)
+(first launch needs the one-time right-click → **Open** Gatekeeper
+approval), [Windows](../install/windows.md), [Linux](../install/linux.md),
+[Docker](../install/docker.md).
+
+## Text-to-speech
+
+| Engine | Guide | Runs on | Cloning | Enabled by |
+|---|---|---|---|---|
+| VoiceStudio (OmniVoice) — **default** | [omnivoice](omnivoice.md) | CUDA · MPS · CPU | ✅ | installed by default |
+| VoxCPM2 | [voxcpm2](voxcpm2.md) | CUDA · MPS · CPU | ✅ + voice design | `pip install "voxcpm>=2.0.3"` |
+| MOSS-TTS-Nano | [moss-tts-nano](moss-tts-nano.md) | CUDA · CPU | ✅ (ref only) | clone + `uv pip install -e .` |
+| KittenTTS | [kittentts](kittentts.md) | CPU | — (8 preset voices) | `pip install kittentts` |
+| MLX-Audio (Kokoro, CSM, Dia, …) | [mlx-audio](mlx-audio.md) | Apple Silicon | model-dependent | `pip install mlx-audio` |
+| CosyVoice 3 | [cosyvoice](cosyvoice.md) | CUDA · CPU | ✅ | clone + requirements |
+| GPT-SoVITS | [gpt-sovits](gpt-sovits.md) | external server | ✅ | its own API server |
+| Sherpa-ONNX | [sherpa-onnx](sherpa-onnx.md) | CUDA · CPU | — | `pip install sherpa-onnx` + model dir |
+| IndexTTS 2.5 | [indextts](indextts.md) | CUDA · CPU | ✅ + emotion | one-click sidecar install |
+| OmniVoice GGUF | [omnivoice-gguf](omnivoice-gguf.md) | CUDA · MPS · CPU | ✅ | bundled binary |
+| Supertonic-3 | [supertonic3](supertonic3.md) | CPU | — (7 preset voices) | `uv sync --extra supertonic` + license |
+| MOSS-TTS-v1.5 (8B) | [moss-tts-v15](moss-tts-v15.md) | CUDA · CPU | ✅ | clone + env var |
+| dots.tts (2B) | [dots-tts](dots-tts.md) | CUDA · CPU (not Windows) | ✅ | clone + env var |
+| OmniVoice (subprocess) | [omnivoice-subprocess](omnivoice-subprocess.md) | CUDA · MPS · CPU | ✅ | opt-in pick, no install |
+| PocketTTS (Kyutai) | [pockettts](pockettts.md) | CPU (not Intel Mac) | ✅ | `uv sync --extra pockettts` + license |
+| Confucius4-TTS | [confucius4-tts](confucius4-tts.md) | CUDA · CPU | ✅ | clone + env var |
+
+## Speech-to-text
+
+| Engine | Guide | Runs on | Best at | Enabled by |
+|---|---|---|---|---|
+| WhisperX | [whisperx](whisperx.md) | CUDA · CPU | dubbing (word timestamps + diarization) | installed by default |
+| Faster-Whisper | [faster-whisper](faster-whisper.md) | CUDA · CPU | general transcription | installed by default |
+| Faster-Whisper (isolated) | [faster-whisper-isolated](faster-whisper-isolated.md) | CUDA · CPU | unattended batches | opt-in pick |
+| MLX Whisper | [mlx-whisper](mlx-whisper.md) | Apple Silicon | Mac default | `pip install mlx-whisper` |
+| PyTorch Whisper | [pytorch-whisper](pytorch-whisper.md) | CUDA · MPS · CPU | ROCm hosts | installed by default |
+| Parakeet TDT (NeMo) | [nemo-parakeet](nemo-parakeet.md) | CUDA · CPU | 25 languages, fast CPU | separate venv (never the app's) |
+| Parakeet TDT (MLX) | [parakeet-mlx](parakeet-mlx.md) | Apple Silicon | dictation, 25 EU languages | default on mac-ARM source installs |
+| Moonshine | [moonshine](moonshine.md) | CPU | edge/low-power, no timestamps | `pip install` (see guide) |
+| FunASR (SenseVoice) | [funasr](funasr.md) | CUDA · CPU | 50+ languages, inline diarization | `pip install funasr` |
+| Sherpa-ONNX dictation | [sherpa-onnx-asr](sherpa-onnx-asr.md) | CPU | live streaming dictation | curated model download |
+| OpenAI-compatible (remote) | [openai-compatible-asr](openai-compatible-asr.md) | network | offloading to a server (audio leaves the machine) | Model Catalogue |
+
+Speaker diarization is not an engine registry of its own — the dub pipeline
+uses pyannote (HF-gated; see [diarization](../features/diarization.md)) and
+FunASR can diarize inline with its `cam++` speaker model.
diff --git a/docs/engines/faster-whisper-isolated.md b/docs/engines/faster-whisper-isolated.md
new file mode 100644
index 00000000..e48d506d
--- /dev/null
+++ b/docs/engines/faster-whisper-isolated.md
@@ -0,0 +1,61 @@
+# VoiceStudio — Faster-Whisper (Crash-Isolated) Engine
+
+The same CTranslate2 Whisper engine as [faster-whisper](faster-whisper.md),
+run in a **separate child process** ("sidecar"). CTranslate2's GPU teardown
+can segfault — the endemic faster-whisper crash — and a hung or crashed
+transcribe in-process takes the whole backend down with it. Isolated, the
+child can crash or be force-killed to reclaim a hung transcribe and its VRAM
+while the backend stays up
+([#730](https://github.com/debpalash/VoiceStudio/issues/730)).
+
+There is nothing extra to install: the sidecar reuses the app's own venv —
+only the process boundary is new.
+
+## Selecting it
+
+- **Model Catalogue → Engines**, ASR tab → **Use** on the crash-isolated row, or
+- pin it with `OMNIVOICE_ASR_BACKEND=faster-whisper-isolated`.
+
+It is never picked by auto-detect — it's an explicit opt-in escape hatch.
+
+## Best at
+
+- **Long batch runs** where one bad file must not kill the backend.
+- Machines where in-process faster-whisper has crashed or hung before:
+  a sidecar crash fails only that job, and the next transcribe respawns a
+  fresh sidecar automatically.
+
+## Platform support
+
+Same as faster-whisper: CUDA float16 or CPU int8 on macOS, Windows, and
+Linux. The sidecar picks cuda/cpu itself and walks the same
+float16 → int8_float16 → int8 degrade chain on GPUs without efficient fp16
+([#551](https://github.com/debpalash/VoiceStudio/issues/551)).
+
+## Model selection
+
+- `ASR_MODEL_FASTER` — the shared model selection, same as the in-process
+  engine: set it once and both variants load the same weights.
+- `ASR_MODEL_FW` — optional sidecar-only override; when set it wins over
+  `ASR_MODEL_FASTER` for this engine. Default `large-v3`.
+- `ASR_COMPUTE_TYPE` — optional: pin the sidecar to one CTranslate2 compute
+  type instead of the automatic degrade chain.
+
+Weights download on first load — see
+[downloading-models](../downloading-models.md).
+
+## Trade-offs and quirks
+
+- **Slightly slower per call** than in-process faster-whisper (IPC overhead);
+  the model stays warm inside the sidecar between calls, so the cost is per
+  request, not per chunk of audio.
+- Word timestamps are Whisper-native (±100–300 ms) — no forced alignment.
+  For dubbing lip-sync, use [whisperx](whisperx.md) or
+  [mlx-whisper](mlx-whisper.md).
+- If the sidecar dies mid-transcription the job fails with a clear
+  "sidecar crashed" error and the backend stays up — retry to respawn.
+- **cuDNN 8 is still required on CUDA** — same CTranslate2 requirement as the
+  in-process engine. It's checked up front so a missing cuDNN 8 shows as
+  "unavailable" in Model Catalogue → Engines instead of a sidecar that
+  silently fails every transcribe
+  ([#1371](https://github.com/debpalash/VoiceStudio/issues/1371)).
diff --git a/docs/engines/faster-whisper.md b/docs/engines/faster-whisper.md
new file mode 100644
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--- /dev/null
+++ b/docs/engines/faster-whisper.md
@@ -0,0 +1,70 @@
+# VoiceStudio — Faster-Whisper Engine
+
+Faster-Whisper runs Whisper on CTranslate2 — the same transcription core
+WhisperX uses, **without** the wav2vec2 forced-alignment pass. It's the safe
+cross-platform fallback when whisperx isn't installed, and the capture/dictation
+fallback on non-Apple machines.
+
+## Selecting it
+
+- **Model Catalogue → Engines**, ASR tab → **Use** on the Faster-Whisper row, or
+- pin it with `OMNIVOICE_ASR_BACKEND=faster-whisper`.
+
+Auto-detect only picks it when [whisperx](whisperx.md) is unavailable.
+
+## Best at
+
+- **Subtitles, dictation buffers, and batch transcription** where Whisper's
+  native word timing (±100–300 ms) is good enough.
+- For dubbing lip-sync, prefer [whisperx](whisperx.md) (or
+  [mlx-whisper](mlx-whisper.md) on Apple Silicon) — their forced alignment is
+  an order of magnitude tighter on word boundaries.
+
+## Platform support
+
+- **CUDA** — float16, with automatic degradation (below).
+- **CPU** — int8 on macOS, Windows, and Linux.
+- **Apple Silicon GPU / ROCm** — not supported: CTranslate2 has no Metal or
+  HIP build, so those hosts run on CPU
+  ([#1529](https://github.com/debpalash/VoiceStudio/issues/1529)); auto-detect
+  routes them to mlx-whisper / pytorch-whisper instead.
+
+## Model selection
+
+`ASR_MODEL_FASTER` — default `Systran/faster-whisper-large-v3`. Accepts the
+size aliases (`tiny` … `large-v3`, `distil-large-v3`) or any CTranslate2
+Whisper repo on HF. Weights download on first load — see
+[downloading-models](../downloading-models.md).
+
+Segments are cleaned up by faster-whisper's built-in Silero VAD before
+transcription.
+
+## Degradation chains
+
+- GPUs without efficient fp16 (older Maxwell/Pascal, GTX 16xx, or a
+  CTranslate2/cuDNN mismatch) fail at model construction with a compute-type
+  error; the engine walks float16 → int8_float16 → int8 instead of failing
+  every chunk ([#551](https://github.com/debpalash/VoiceStudio/issues/551)).
+- A CUDA out-of-memory falls back to CPU (slower, same model and accuracy) —
+  flushing the resident TTS model frees VRAM for GPU-speed ASR
+  ([#255](https://github.com/debpalash/VoiceStudio/issues/255)).
+
+## Quirks
+
+- **cuDNN 8 required on CUDA** — a missing cuDNN 8 would fast-fail the whole
+  process, so the engine checks up front and reports itself unavailable
+  instead ([#1371](https://github.com/debpalash/VoiceStudio/issues/1371)).
+  pytorch-whisper covers that case on torch's bundled cuDNN 9.
+- On some hardened Linux kernels the CTranslate2 native library is rejected
+  with "cannot enable executable stack" (an OSError, not an ImportError) —
+  reported as unavailable rather than crashing engine selection
+  ([#692](https://github.com/debpalash/VoiceStudio/issues/692)).
+- CTranslate2's GPU teardown can rarely segfault the process at unload. If
+  you hit that, switch to the crash-isolated variant —
+  [faster-whisper-isolated](faster-whisper-isolated.md)
+  ([#730](https://github.com/debpalash/VoiceStudio/issues/730)).
+- Transcribes are time-bounded: `OMNIVOICE_TRANSCRIBE_CHUNK_TIMEOUT_S`
+  (default 120 s per dub chunk) and `OMNIVOICE_ASR_TRANSCRIBE_TIMEOUT_S`
+  (default 300 s whole-file).
+
+Speed comparisons across engines live in [performance](../performance.md).
diff --git a/docs/engines/funasr.md b/docs/engines/funasr.md
new file mode 100644
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--- /dev/null
+++ b/docs/engines/funasr.md
@@ -0,0 +1,62 @@
+# VoiceStudio — FunASR (SenseVoice) Engine
+
+FunASR drives Alibaba's SenseVoiceSmall with FSMN-VAD: an all-in-one
+multilingual pipeline — transcription with punctuation and inverse text
+normalization across **50+ languages**, plus optional **inline speaker
+diarization** via the cam++ speaker model. It's the opt-in alternative to
+WhisperX ([#182](https://github.com/debpalash/VoiceStudio/issues/182));
+WhisperX remains the cross-platform default.
+
+## Selecting it
+
+- Install it into the app venv: `uv pip install funasr`.
+- Then **Model Catalogue → Engines**, ASR tab → **Use** on the FunASR row, or
+  `OMNIVOICE_ASR_BACKEND=funasr`.
+
+Auto-detect never picks it; it's an explicit opt-in.
+
+## Best at
+
+- **Multi-speaker transcription without any HuggingFace token.** This is the
+  only ASR engine with diarization built in: cam++ labels each sentence
+  (`Speaker 1`, `Speaker 2`, ...) in the same pass — no gated pyannote
+  model, no license click-through. Compare
+  [diarization](../features/diarization.md) for the pyannote/WhisperX route
+  and what each buys you.
+- **Broad language coverage** beyond Whisper's strongest languages, with
+  punctuation included.
+
+## Not suited for
+
+- **Lip-sync dubbing** — FunASR returns sentence-level timestamps, not
+  word-level ones. Use [whisperx](whisperx.md) /
+  [mlx-whisper](mlx-whisper.md) when word timing matters.
+
+## Platform support
+
+CUDA or CPU, on macOS, Windows, and Linux.
+
+## Model selection
+
+| Variable | Default | Role |
+| --- | --- | --- |
+| `ASR_MODEL_FUNASR` | `iic/SenseVoiceSmall` | main ASR model |
+| `ASR_FUNASR_VAD` | `fsmn-vad` | VAD segmentation model |
+| `ASR_FUNASR_SPK` | `cam++` | speaker model; set to empty (`ASR_FUNASR_SPK=`) to disable diarization and use the dub pipeline's pyannote/heuristic path instead |
+
+Weights download on first load (through FunASR's own model hub) — see
+[downloading-models](../downloading-models.md).
+
+## Quirks
+
+- With the speaker model enabled, long recordings are transcribed in **one
+  call** and split by FunASR's internal VAD — cam++ assigns speaker cluster
+  IDs per call, so this is what keeps "Speaker 1" meaning the same person
+  across the whole file.
+- The engine runs with `spk_mode="vad_segment"`: FunASR 1.3.1's default
+  (`punc_segment`) requires a separate punctuation model and crashes when
+  SenseVoice is loaded without one.
+- SenseVoice's rich-token markup (language/emotion/event tags around the
+  text) is stripped from the output automatically.
+- Language detection is automatic (`language: auto`); the detected language
+  is reported per file.
diff --git a/docs/engines/gpt-sovits.md b/docs/engines/gpt-sovits.md
new file mode 100644
index 00000000..0aa1f36d
--- /dev/null
+++ b/docs/engines/gpt-sovits.md
@@ -0,0 +1,78 @@
+# VoiceStudio — GPT-SoVITS Engine
+
+GPT-SoVITS (RVC-Boss) is one of the most popular open-source voice-cloning
+systems (57k+ GitHub stars, MIT-licensed). It does zero-shot and few-shot
+cloning with excellent naturalness in Chinese, English, Japanese, Cantonese,
+and Korean, and it is very fast (RTF ~0.014 on suitable hardware).
+
+Unlike VoiceStudio's other engines, GPT-SoVITS does not run inside the app.
+It ships as a standalone API server, and VoiceStudio connects to it over
+HTTP.
+
+## When to pick it
+
+- You already run (or want to run) a GPT-SoVITS server, e.g. with few-shot
+  fine-tuned voices.
+- You need fast, natural cloning in zh/en/ja/yue/ko.
+
+## Setup
+
+1. Install and start the GPT-SoVITS API server (upstream project):
+
+   ```bash
+   cd GPT-SoVITS
+   python api_v2.py -a 127.0.0.1 -p 9880 -c GPT_SoVITS/configs/tts_infer.yaml
+   ```
+
+2. Select the engine via **Model Catalogue → Engines** or
+   `OMNIVOICE_TTS_BACKEND=gpt-sovits`.
+
+VoiceStudio marks the engine available only when the server responds
+(2-second reachability probe).
+
+## Configuration
+
+| Variable | Default | Meaning |
+| --- | --- | --- |
+| `OMNIVOICE_GPTSOVITS_URL` | `http://127.0.0.1:9880` | API server URL |
+| `OMNIVOICE_TRUSTED_NETWORKS` | (unset) | Required to allow a non-loopback server |
+
+**Remote servers:** by default VoiceStudio only talks to loopback addresses
+— part of the local-first guarantee. To point at a server on another
+machine (e.g. a GPU box on your LAN), add its network to
+`OMNIVOICE_TRUSTED_NETWORKS`; otherwise the connection is refused as an
+untrusted endpoint.
+
+Prefer `https://` (or a private tunnel such as Tailscale/WireGuard) for any
+non-loopback server: with plain `http://` the text you synthesize and the
+audio that comes back cross the network unencrypted. VoiceStudio does not
+disable certificate verification, so a TLS endpoint needs a certificate the
+system trusts.
+
+## Behaviour notes
+
+- Output is 32 kHz mono (server output is resampled if needed).
+- Cloning passes your reference clip path and optional transcript to the
+  server; the reference path must be readable **by the server process**, so
+  remote servers need the clip on their own filesystem.
+- Speed control is forwarded as the server's `speed_factor`.
+- The GPU is whatever the GPT-SoVITS server itself uses (CUDA preferred);
+  VoiceStudio's side is just an HTTP client.
+
+## Known limits
+
+- Five languages only; for broader coverage use
+  [OmniVoice](omnivoice.md) ([languages.md](../languages.md)).
+- No voice design; server availability is your responsibility — if the
+  server stops, generations fail with a "server not reachable" error.
+
+## Troubleshooting
+
+- "GPT-SoVITS server not reachable": start the server with the command
+  above, or fix `OMNIVOICE_GPTSOVITS_URL`.
+- "endpoint is outside loopback or OMNIVOICE_TRUSTED_NETWORKS": see
+  Configuration above.
+- Other issues: [install/troubleshooting.md](../install/troubleshooting.md).
+
+See also: [benchmarks.md](../benchmarks.md),
+[expressive-speech.md](../expressive-speech.md).
diff --git a/docs/engines/kittentts.md b/docs/engines/kittentts.md
new file mode 100644
index 00000000..943a30fe
--- /dev/null
+++ b/docs/engines/kittentts.md
@@ -0,0 +1,75 @@
+# VoiceStudio — KittenTTS Engine
+
+KittenTTS (KittenML) is the lightweight English "flash" tier: a 25–80 MB
+ONNX model with 8 preset voices that runs realtime on any CPU — no torch, no
+CUDA, no GPU of any kind. Use it when you just need quick English narration
+(voiceovers, demo reads, short phrases) with no reference sample.
+
+## When to pick it
+
+- English-only content where speed and a tiny install matter more than
+  cloning.
+- Machines with no usable GPU.
+
+The trade-off against [OmniVoice](omnivoice.md): no voice cloning, English
+only — but a much faster and much smaller install.
+
+## Setup
+
+```bash
+pip install kittentts
+```
+
+Then select the engine via **Model Catalogue → Engines** or
+`OMNIVOICE_TTS_BACKEND=kittentts`.
+
+## Voices
+
+Eight preset voices, four male/female pairs:
+
+```text
+expr-voice-2-m  expr-voice-2-f   (default: expr-voice-2-f)
+expr-voice-3-m  expr-voice-3-f
+expr-voice-4-m  expr-voice-4-f
+expr-voice-5-m  expr-voice-5-f
+```
+
+An unknown voice id logs an info message and falls back to the default.
+
+## Model selection
+
+| Variable | Default | Meaning |
+| --- | --- | --- |
+| `OMNIVOICE_KITTENTTS_MODEL` | `KittenML/kitten-tts-mini-0.8` | HuggingFace checkpoint to load |
+
+The ~80 MB model downloads from HuggingFace on first use (retried once on a
+flaky connection). See [downloading-models.md](../downloading-models.md).
+
+## Behaviour notes
+
+- Output is 24 kHz mono.
+- CPU-only by design — the ONNX graph has no CUDA/MPS path.
+- Non-English `language` values are ignored with a log line pointing at
+  OmniVoice; reference audio is likewise ignored (no cloning).
+- **Long-input hardening
+  ([#1173](https://github.com/debpalash/VoiceStudio/issues/1173)):** the
+  shipped ONNX graph has a hard 512-token cap, and phonemization can expand
+  text massively (digits especially). VoiceStudio pre-measures every chunk
+  with the model's own tokenizer and splits oversized chunks at word
+  boundaries, so long or digit-heavy inputs no longer abort inside
+  onnxruntime with an opaque "invalid expand shape" error.
+
+## Known limits
+
+- English only; no cloning, no voice design, no emotion controls
+  (see [expressive-speech.md](../expressive-speech.md)).
+- Preset voices only — speed is the one knob.
+
+## Troubleshooting
+
+- Engine unavailable: `pip install kittentts` into VoiceStudio's Python
+  environment and restart.
+- Other issues: [install/troubleshooting.md](../install/troubleshooting.md).
+
+See also: [benchmarks.md](../benchmarks.md),
+[disk usage](disk-usage.md).
diff --git a/docs/engines/mlx-audio.md b/docs/engines/mlx-audio.md
new file mode 100644
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--- /dev/null
+++ b/docs/engines/mlx-audio.md
@@ -0,0 +1,76 @@
+# VoiceStudio — MLX-Audio Engine (Apple Silicon)
+
+MLX-Audio (Blaizzy/mlx-audio) wraps 14+ TTS engines — Kokoro, CSM, Dia,
+Qwen3-TTS, Chatterbox, MeloTTS, OuteTTS, and more — behind a single adapter
+that runs on Apple's MLX framework. It is **Apple Silicon only**: the engine
+is not shipped on Linux, Windows, or Intel Macs, and a stray wheel on those
+platforms never reports as available
+([#390](https://github.com/debpalash/VoiceStudio/issues/390)).
+
+## When to pick it
+
+- You're on an M-series Mac and want small, fast models tuned for it.
+- You want one of the specific hosted models (Kokoro for small multilingual,
+  CSM for cloning, Qwen3-TTS for voice design, Dia for dialogue, …).
+
+## Setup
+
+```bash
+pip install mlx-audio
+```
+
+Then select the engine via **Model Catalogue → Engines** or
+`OMNIVOICE_TTS_BACKEND=mlx-audio`.
+
+## Model selection
+
+One backend hosts many models. The curated set:
+
+| Key | Model | Niche |
+| --- | --- | --- |
+| `kokoro` (default) | `mlx-community/Kokoro-82M-bf16` | small multilingual |
+| `csm` | `mlx-community/csm-1b-8bit` | voice cloning |
+| `qwen3-tts` | `mlx-community/Qwen3-TTS-12Hz-1.7B-VoiceDesign-4bit` | voice design |
+| `dia` | `mlx-community/Dia-1.6B` | dialogue |
+| `chatterbox` | `mlx-community/Chatterbox-TTS-4bit` | expressive |
+| `melotts` | `mlx-community/MeloTTS-English-v3-MLX` | lightweight VITS |
+| `outetts` | `mlx-community/Llama-OuteTTS-1.0-1B-4bit` | LM-based |
+
+Pick a model in the **Model Catalogue → Engines** curated picker
+([#981](https://github.com/debpalash/VoiceStudio/issues/981)) or set
+`OMNIVOICE_MLX_AUDIO_MODEL` to either a curated key (`kokoro`) or any full
+HF repo id. The env var overrides the persisted UI choice.
+
+## Behaviour notes
+
+- Output is 24 kHz mono for most hosted models.
+- **Cloning works only with the `csm` model** — it is the only curated model
+  confirmed to accept a reference clip. Other models silently ignore
+  reference audio, so the engine reports cloning support only when CSM is
+  selected (dub/batch jobs gate on this).
+- Voice design (text description → voice) is available through the
+  Qwen3-TTS VoiceDesign model.
+- Language support is per-model (Kokoro ~8 languages, others vary). An
+  unsupported language for Kokoro produces a clear error naming what it
+  does support ([#977](https://github.com/debpalash/VoiceStudio/issues/977))
+  — leave language on Auto or switch to a multilingual engine.
+
+## Platform notes
+
+This engine is exempt from cross-platform parity as a platform-only
+capability behind explicit opt-in: it exists only where Apple's MLX runtime
+exists. On any other platform the engine picker shows it unavailable with
+the reason.
+
+## Troubleshooting
+
+- Unavailable on an M-series Mac: `pip install mlx-audio` into
+  VoiceStudio's Python environment; in a packaged app build, MLX's native
+  libraries may fail to load — the engine reports unavailable rather than
+  crashing.
+- Other issues: [install/troubleshooting.md](../install/troubleshooting.md).
+
+See also: [benchmarks.md](../benchmarks.md),
+[languages.md](../languages.md),
+[downloading-models.md](../downloading-models.md),
+[disk usage](disk-usage.md).
diff --git a/docs/engines/mlx-whisper.md b/docs/engines/mlx-whisper.md
new file mode 100644
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--- /dev/null
+++ b/docs/engines/mlx-whisper.md
@@ -0,0 +1,57 @@
+# VoiceStudio — MLX Whisper Engine
+
+MLX Whisper runs Whisper on the Apple Silicon GPU via MLX. It exists because
+CTranslate2 (whisperx / faster-whisper) has **no Metal build** — on a Mac
+those engines transcribe on the CPU no matter what GPU is present. Measured
+on an M2 with whisper-large-v3, one 30 s dub chunk: **90.4 s on WhisperX
+(CPU) vs 20.5 s on MLX (GPU)** — which is why auto-detect picks MLX Whisper
+on every Apple Silicon machine
+([#1127](https://github.com/debpalash/VoiceStudio/issues/1127)).
+
+## Selecting it
+
+- Nothing to do on Apple Silicon — auto-detect prefers it there.
+- Or explicitly: **Model Catalogue → Engines**, ASR tab → **Use**, or
+  `OMNIVOICE_ASR_BACKEND=mlx-whisper`.
+
+## Best at
+
+- **Dubbing on a Mac** — it layers the same wav2vec2 forced alignment
+  WhisperX uses on top of the GPU transcription, so word timing (±10–30 ms)
+  and therefore lip-sync accuracy are unchanged. Same model, same alignment,
+  ~4x the speed.
+- **Dictation/capture** — the capture path automatically swaps in
+  `mlx-community/whisper-large-v3-turbo` (~5x faster than large-v3) unless a
+  sherpa dictation model or [parakeet-mlx](parakeet-mlx.md) is preferred.
+
+## Platform support
+
+**Apple Silicon only.** A shared platform gate refuses Linux, Windows, and
+Intel Macs before any package import, so a stray `mlx-whisper` wheel on the
+wrong platform never reports itself available
+([#390](https://github.com/debpalash/VoiceStudio/issues/390)). All other
+platforms use the CUDA/CPU engines instead.
+
+## Model selection
+
+- `ASR_MODEL` — default `mlx-community/whisper-large-v3-mlx`. Any MLX-format
+  Whisper repo works. Weights download on first load — see
+  [downloading-models](../downloading-models.md).
+- `OMNIVOICE_ALIGN_DEVICE` — force the wav2vec2 aligner's device. The aligner
+  runs on MPS when it can and falls back to CPU; languages without a bundled
+  aligner (~20 major languages have one) keep Whisper's native word
+  timestamps.
+
+## Quirks
+
+- Audio is decoded through VoiceStudio's validated ffmpeg rather than the
+  bare `ffmpeg` PATH lookup mlx-whisper would do on its own — a clean
+  from-source install with no system ffmpeg works fine
+  ([#479](https://github.com/debpalash/VoiceStudio/issues/479)).
+- The model is warmed into unified memory in the background, so the first
+  transcribe after startup doesn't pay the load cost.
+- In a packaged app, a native MLX library that fails to load is reported as
+  "unavailable" (with fallback to another engine) rather than crashing the
+  engine list.
+
+Speed comparisons across engines live in [performance](../performance.md).
diff --git a/docs/engines/moonshine.md b/docs/engines/moonshine.md
new file mode 100644
index 00000000..02d85f59
--- /dev/null
+++ b/docs/engines/moonshine.md
@@ -0,0 +1,48 @@
+# VoiceStudio — Moonshine Engine
+
+Moonshine is an edge-optimized ASR family built for CPU-only machines.
+Unlike Whisper it processes variable-length audio (no padding everything to
+30 s), which keeps latency low on short clips — sub-200 ms class on capture
+buffers. It's the lightest local option for quick transcription on hardware
+where even int8 whisper-large is too slow.
+
+## Selecting it
+
+- Install one of the runtimes into the app venv:
+  `uv pip install moonshine-onnx` (lighter, tried first) or
+  `moonshine-voice`.
+- Then **Model Catalogue → Engines**, ASR tab → **Use** on the Moonshine row,
+  or `OMNIVOICE_ASR_BACKEND=moonshine`.
+
+Auto-detect never picks it; it's an explicit opt-in.
+
+## Best at
+
+- **Quick notes and short-clip transcription on low-power CPU machines.**
+- Environments where a sub-1 GB footprint matters more than word timing or
+  language coverage.
+
+## Not suited for
+
+- **Dubbing.** Output is plain text as a **single segment spanning the whole
+  file — no word or segment timestamps** — so there's nothing for lip-sync
+  or subtitle timing to work with. Use a Whisper-family engine or
+  [sherpa-onnx-asr](sherpa-onnx-asr.md) for those jobs.
+- Multilingual work: results report English; for broad language coverage use
+  [whisperx](whisperx.md) or [funasr](funasr.md).
+
+## Platform support
+
+CPU only, by design — macOS, Windows, and Linux. It claims no GPU.
+
+## Model selection
+
+`ASR_MODEL_MOONSHINE` — default `moonshine/base`. Weights download on first
+load — see [downloading-models](../downloading-models.md).
+
+## Quirks
+
+- The engine tries `moonshine_onnx` first and falls back to
+  `moonshine_voice` — installing either one is enough.
+- Segment bounds are synthesized from the audio duration (start 0, end =
+  file length), since the model reports none.
diff --git a/docs/engines/moss-tts-nano.md b/docs/engines/moss-tts-nano.md
new file mode 100644
index 00000000..286891a5
--- /dev/null
+++ b/docs/engines/moss-tts-nano.md
@@ -0,0 +1,78 @@
+# VoiceStudio — MOSS-TTS-Nano Engine
+
+MOSS-TTS-Nano (OpenMOSS) is the low-resource, broad-language pick: a
+100M-parameter autoregressive codec LM that runs realtime on a 4-core CPU —
+no GPU required — with native 48 kHz output and 20 languages under an
+Apache-2.0 license. It fills the "runs on a fanless laptop" tier while still
+covering languages like Arabic, Hebrew, Persian, Korean, and Turkish.
+
+## When to pick it
+
+- CPU-only or low-power hardware, but you still need cloning and non-English
+  coverage.
+- Your language is among: Chinese, English, German, Spanish, French,
+  Japanese, Italian, Hebrew, Korean, Russian, Persian, Arabic, Polish,
+  Portuguese, Czech, Danish, Swedish, Hungarian, Greek, Turkish.
+
+## Setup
+
+The package is **not on PyPI** — install it from the upstream repo into
+VoiceStudio's Python environment:
+
+```bash
+git clone https://github.com/OpenMOSS/MOSS-TTS-Nano.git
+cd MOSS-TTS-Nano
+uv pip install -e .
+```
+
+Then select the engine via **Model Catalogue → Engines** or
+`OMNIVOICE_TTS_BACKEND=moss-tts-nano`.
+
+## Model selection
+
+| Variable | Default | Meaning |
+| --- | --- | --- |
+| `OMNIVOICE_MOSS_TTS_MODEL` | `OpenMOSS-Team/MOSS-TTS-Nano` | HuggingFace checkpoint to load |
+
+The first use downloads the weights (retried once on a truncated download).
+See [downloading-models.md](../downloading-models.md).
+
+## Behaviour notes
+
+- **Cloning is reference-only**: pass a reference clip. Style instructions,
+  preset speakers, and speed control are not supported and are silently
+  ignored, so mixed-engine call sites keep working.
+- The model emits 48 kHz stereo; VoiceStudio downmixes to mono, matching the
+  rest of the pipeline (the dub mixer treats TTS output as mono per
+  segment).
+- Runs on CPU or CUDA.
+
+## Upstream is unpinned
+
+The upstream repo is installed straight from git with no pinned release, and
+the model class it exports has changed before
+([#1287](https://github.com/debpalash/VoiceStudio/issues/1287)). VoiceStudio
+therefore verifies that a usable model class actually exists — not just that
+the package imports — before reporting the engine as ready. If the engine
+shows unavailable with a "does not expose a usable model class" message,
+pull the latest upstream and re-run `uv pip install -e .`, or open an issue
+with the version you have.
+
+## Known limits
+
+- No voice design, no instruct, no speed control — cloning from a reference
+  clip only.
+- Quality sits below the large engines; see
+  [benchmarks.md](../benchmarks.md).
+
+## Troubleshooting
+
+- "moss_tts_nano package not installed": run the clone + `uv pip install -e .`
+  steps above.
+- Entry-point errors after an upstream update: see "Upstream is unpinned"
+  above.
+- General issues: [install/troubleshooting.md](../install/troubleshooting.md).
+
+See also: [languages.md](../languages.md),
+[expressive-speech.md](../expressive-speech.md),
+[disk usage](disk-usage.md).
diff --git a/docs/engines/nemo-parakeet.md b/docs/engines/nemo-parakeet.md
new file mode 100644
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--- /dev/null
+++ b/docs/engines/nemo-parakeet.md
@@ -0,0 +1,58 @@
+# VoiceStudio — Parakeet TDT (NVIDIA NeMo) Engine
+
+NVIDIA's Parakeet TDT via the NeMo toolkit: a FastConformer encoder with a
+Token-and-Duration Transducer decoder. It beats Whisper large-v3 on English
+benchmarks (~6% WER) and supports **25 (mostly European) languages** with
+automatic language detection. The 0.6B model is fast even on CPU — measured
+RTF 0.08–0.23 on an Apple Silicon M2 CPU (2026-07-02), ~20x faster than
+faster-whisper large-v3 int8 on the same host.
+
+## Do not install NeMo into the app venv
+
+`nemo_toolkit`'s ASR extras pin `transformers>=4.57,<4.58`, which conflicts
+with VoiceStudio's own `transformers>=5.3` requirement and **will break the
+backend** (ImportError on startup) if installed into the shared venv. There
+is currently no safe in-app install path for this engine; in-app isolation
+is tracked separately.
+
+If you want the Parakeet models without a separate environment, use these
+instead — same model family, no NeMo dependency:
+
+- **Apple Silicon:** [parakeet-mlx](parakeet-mlx.md) (installed by default on
+  mac-ARM source installs).
+- **Any platform, CPU:** [sherpa-onnx-asr](sherpa-onnx-asr.md) — its default
+  dictation model is an int8 ONNX export of Parakeet TDT v3.
+
+## Selecting it
+
+Only meaningful if you've set up `nemo_toolkit[asr]` in a **separate,
+dedicated Python environment** that runs the backend:
+
+- **Model Catalogue → Engines**, ASR tab → **Use** on the Parakeet TDT row, or
+- `OMNIVOICE_ASR_BACKEND=nemo-parakeet`.
+
+Auto-detect never picks it; it's an explicit opt-in.
+
+## Best at
+
+- **English and European-language transcription** where WER matters more
+  than word-level subtitle timing.
+- **CPU-only hosts** — faster than realtime without any GPU.
+
+## Platform support
+
+CUDA or CPU (the old hard CUDA gate was removed — see the RTF numbers
+above). Availability is a pure dependency check on `nemo.collections.asr`.
+
+## Model selection
+
+`ASR_MODEL_NEMO` — default `nvidia/parakeet-tdt-0.6b-v3`. Weights download
+on first load — see [downloading-models](../downloading-models.md).
+
+## Quirks
+
+- Output is a **single segment** for the whole file (NeMo doesn't VAD-split
+  like Whisper), with word timestamps when the model exposes them — fine for
+  dictation and plain transcripts, not ideal for long-form subtitles.
+- The detected language isn't exposed cleanly by NeMo, so results report
+  `en` regardless of the actual (auto-detected) language.
diff --git a/docs/engines/omnivoice-gguf.md b/docs/engines/omnivoice-gguf.md
new file mode 100644
index 00000000..5010f522
--- /dev/null
+++ b/docs/engines/omnivoice-gguf.md
@@ -0,0 +1,83 @@
+# VoiceStudio — OmniVoice GGUF Engine
+
+OmniVoice GGUF runs the same OmniVoice model as the [default
+engine](omnivoice.md), but through a bundled native binary
+(`bin/omnivoice-tts-<platform>`) loading quantized GGUF weights. It is
+hardware-adaptive: a probe picks the quantization that fits your machine, so
+small GPUs and CPU-only hosts get a working OmniVoice instead of a paging,
+timing-out one.
+
+## When to pick it
+
+- Your GPU is below the default engine's 6 GB VRAM floor.
+- CPU-only machines that still want OmniVoice's voice and language coverage.
+- You want generation isolated in a separate process (a crash or leak never
+  takes the app down — each generation spawns the binary fresh).
+
+## Quantization selection
+
+Weights come from the `Serveurperso/OmniVoice-GGUF` HuggingFace repo, pinned
+to an exact revision. The hardware probe selects:
+
+| Hardware | Quant | Approx. VRAM use |
+| --- | --- | --- |
+| 12 GB+ VRAM | BF16 | ~1.6 GB (quality-first) |
+| 4–12 GB VRAM | Q8_0 | ~945 MB (recommended balance) |
+| 1–4 GB VRAM | Q4_K_M | ~659 MB (minimal footprint) |
+| CPU-only | Q4_K_M | RAM-bound, latency-tolerable |
+
+You can override the selection from Settings; overrides are allow-listed
+against the same table (an F32 reference quant, ~3.2 GB, is override-only).
+
+## Setup
+
+Nothing to install: installer and CI builds bundle the binary for your
+platform. Select the engine via **Model Catalogue → Engines** or
+`OMNIVOICE_TTS_BACKEND=omnivoice-gguf`. The quant weights download on first
+use (see [downloading-models.md](../downloading-models.md)) — install them
+ahead of time from **Model Catalogue → Models** if you want the first
+generation to be quick; a long first render is the download, not a hang.
+
+**Source checkouts:** the repo ships zero-byte placeholders in `bin/` — real
+binaries come from CI or the installer. The engine detects a placeholder and
+reports unavailable with instructions
+([#1172](https://github.com/debpalash/VoiceStudio/issues/1172)) instead of
+failing at spawn time; build one with
+`scripts/build-omnivoice-tts.sh --platform <slug>` or use the default
+in-process engine.
+
+## Integrity and self-healing
+
+Before reporting ready, the engine:
+
+- verifies the binary against the SHA-256 manifest (`bin/checksums.sha256`);
+- detects macOS Gatekeeper quarantine and prints the exact
+  `xattr -cr '/Applications/VoiceStudio.app'` fix;
+- restores a missing execute bit (a git clone or zip extract on POSIX can
+  drop `+x`, which used to surface as a permission error mislabeled as
+  out-of-memory — [#437](https://github.com/debpalash/VoiceStudio/issues/437)).
+  The chmod runs only after the SHA check confirms it's the right file.
+
+## Behaviour notes
+
+- Output is 24 kHz mono — same model, same rate as in-process OmniVoice.
+- Cloning from a reference clip (with optional transcript) and style
+  instructions are supported; no voice design.
+- Same multilingual surface as OmniVoice ([languages.md](../languages.md)).
+- Because generation runs in another process, the app's own GPU counters
+  don't see its allocations — diagnostics label it accordingly.
+
+| Variable | Default | Meaning |
+| --- | --- | --- |
+| `OMNIVOICE_GGUF_GENERATE_TIMEOUT_S` | (generous built-in) | Per-generation timeout for the spawned binary |
+
+## Troubleshooting
+
+- "GGUF binary missing": this build doesn't bundle the runtime for your
+  platform — use the default engine.
+- Checksum mismatch or quarantine messages: follow the printed fix, or
+  reinstall.
+- Other issues: [install/troubleshooting.md](../install/troubleshooting.md).
+
+See also: [benchmarks.md](../benchmarks.md),
+[performance.md](../performance.md), [disk usage](disk-usage.md).
diff --git a/docs/engines/omnivoice.md b/docs/engines/omnivoice.md
new file mode 100644
index 00000000..90b60055
--- /dev/null
+++ b/docs/engines/omnivoice.md
@@ -0,0 +1,74 @@
+# VoiceStudio — OmniVoice Engine (default)
+
+OmniVoice (k2-fsa/OmniVoice) is VoiceStudio's default TTS engine — the one a
+fresh install uses without any configuration. It does zero-shot voice cloning
+across 600+ languages and outputs 24 kHz mono audio. Voice cloning, dubbing,
+and dictation all run on it out of the box.
+
+## When to pick it
+
+- You want cloning plus the broadest language coverage (see
+  [languages.md](../languages.md)).
+- You have a GPU (CUDA or Apple Silicon MPS) with ~6 GB VRAM or more.
+- You just installed VoiceStudio — it's already selected.
+
+For low-VRAM or CPU-only machines, the
+[OmniVoice GGUF](omnivoice-gguf.md) variant runs the same model through a
+quantized native binary with a much smaller memory footprint.
+
+## Requirements
+
+- Runs on CUDA, MPS (Apple Silicon), or CPU — auto-detected.
+- Recommended VRAM floor: **6 GB** on a dedicated GPU. This is the only
+  engine with a measured floor: on 4 GB cards (GTX 1650 Ti, Quadro P2000 —
+  issues [#1226](https://github.com/debpalash/VoiceStudio/issues/1226) /
+  [#1222](https://github.com/debpalash/VoiceStudio/issues/1222)) the driver
+  pages to system RAM and a render that should take seconds runs for minutes
+  until the compute budget kills it. The UI warns before you wait; nothing
+  hard-blocks, since short inputs can still fit.
+- No extra install — the model ships with the app and downloads its weights
+  on first use (see [downloading-models.md](../downloading-models.md)).
+
+## Selecting the engine
+
+OmniVoice is the default, so normally there is nothing to do. If you switched
+away and want it back:
+
+- **Model Catalogue → Engines**, or
+- set `OMNIVOICE_TTS_BACKEND=omnivoice`.
+
+The env var overrides the persisted UI choice.
+
+## Behaviour notes
+
+- Weights load lazily on first use and are shared with the rest of the app
+  (dubbing, dictation) — the model is never double-loaded.
+- On CUDA the model runs fp16 with `torch.compile`; a speech recognizer is
+  co-loaded for the cloning path.
+- Output is 24 kHz mono; the shared mastering chain (highpass + compressor)
+  is tuned for this rate and applied automatically.
+- Cloning takes a short reference clip (`ref_audio`); an optional transcript
+  of the clip improves conditioning.
+
+## Known limits
+
+- No voice design from a text description — use [VoxCPM2](voxcpm2.md) for
+  that.
+- Below the 6 GB VRAM floor, expect very slow renders or budget timeouts;
+  prefer [OmniVoice GGUF](omnivoice-gguf.md) or a CPU engine such as
+  [PocketTTS](pockettts.md).
+
+## Troubleshooting
+
+- "Too heavy for the available compute" on a small GPU: see the VRAM floor
+  above — switch to OmniVoice GGUF or close other GPU apps.
+- First generation is slow: the first call downloads multi-GB weights. To
+  keep the first render quick, install the model ahead of time from
+  **Model Catalogue → Models** — a long first generate is almost always the
+  download, not a hang.
+- General install issues: [install/troubleshooting.md](../install/troubleshooting.md).
+
+See also: [benchmarks.md](../benchmarks.md),
+[performance.md](../performance.md),
+[expressive-speech.md](../expressive-speech.md),
+[disk usage](disk-usage.md).
diff --git a/docs/engines/parakeet-mlx.md b/docs/engines/parakeet-mlx.md
new file mode 100644
index 00000000..22e43a71
--- /dev/null
+++ b/docs/engines/parakeet-mlx.md
@@ -0,0 +1,58 @@
+# VoiceStudio — Parakeet TDT v3 (MLX) Engine
+
+NVIDIA's Parakeet TDT v3 on the Apple Silicon GPU, via the small pure-Python
+`parakeet-mlx` package. It gives Macs the Parakeet tier CUDA/CPU users get
+through NeMo or sherpa-onnx: **25 European languages**, word timestamps from
+the TDT decoder itself (no wav2vec2 alignment pass needed), ~1.2 GB download,
+~2 GB unified memory, dictation-grade speed on the GPU.
+
+Unlike [nemo-parakeet](nemo-parakeet.md) it needs no `nemo_toolkit` (whose
+transformers pin conflicts with the app's) — it is **installed by default on
+Apple Silicon source installs since 0.3.22**.
+
+## Selecting it
+
+- **Model Catalogue → Engines**, ASR tab → **Use** on the Parakeet TDT v3
+  (MLX) row, or `OMNIVOICE_ASR_BACKEND=parakeet-mlx`.
+- **Dictation prefers it automatically**: once the model weights are
+  installed (Model Catalogue → Models — the auto-pick never triggers a
+  download), live dictation/capture uses it whenever your system language is
+  one of the 25 covered European languages. Other languages keep the
+  multilingual Whisper engine, so dictation coverage never regresses.
+
+## Best at
+
+- **Live dictation on a Mac** — TDT decoding is fast enough for the capture
+  path, at Parakeet's better-than-Whisper English WER.
+- **European-language transcription** with word timestamps at a fraction of
+  whisper-large-v3's memory and compute.
+
+For languages outside the 25 (CJK, Arabic, ...), use
+[mlx-whisper](mlx-whisper.md) instead.
+
+## Platform support
+
+**Apple Silicon only** — the same shared MLX platform gate as mlx-whisper
+refuses Linux, Windows, and Intel Macs before any import
+([#390](https://github.com/debpalash/VoiceStudio/issues/390)). It runs on the
+unified-memory GPU; there is no CPU tier.
+
+## Model selection
+
+`ASR_MODEL_PARAKEET_MLX` — default `mlx-community/parakeet-tdt-0.6b-v3`.
+Weights download on first load — see
+[downloading-models](../downloading-models.md).
+
+## Quirks
+
+- Long files are processed in 120 s chunks internally to bound unified-memory
+  use; short dictation buffers and dub chunks are unaffected.
+- Parakeet v3 auto-detects among its 25 languages but doesn't expose the
+  pick, so the reported language is the one you requested (or none) — it is
+  never hardcoded to English.
+- Word timestamps are merged from the decoder's subword tokens — good for
+  subtitles and dictation; for lip-sync-critical dubbing the wav2vec2-aligned
+  engines ([mlx-whisper](mlx-whisper.md), [whisperx](whisperx.md)) remain the
+  accuracy tier.
+
+Speed comparisons across engines live in [performance](../performance.md).
diff --git a/docs/engines/pockettts.md b/docs/engines/pockettts.md
new file mode 100644
index 00000000..9084074a
--- /dev/null
+++ b/docs/engines/pockettts.md
@@ -0,0 +1,82 @@
+# VoiceStudio — PocketTTS Engine
+
+PocketTTS (kyutai-labs/pocket-tts, 100M parameters) is the fastest-CPU-render
+pick: small, low-latency, CPU-only, with zero-shot voice cloning from a
+reference clip. It covers six languages — English, French, German,
+Portuguese, Italian, Spanish — with one model per language, and measures
+roughly 8–9x real-time on an Apple M3 Pro.
+
+It complements the quality engines: where they fall back to CPU, PocketTTS
+is built for it. CPU-only is deliberate — upstream observes no GPU speedup
+for this model.
+
+## When to pick it
+
+- CPU-only machines that need fast rendering *and* voice cloning.
+- Latency-sensitive use (dictation-style, short utterances) in one of the
+  six languages.
+
+## Setup
+
+1. Install the optional dependency:
+
+   ```bash
+   uv sync --extra pockettts
+   ```
+
+   (Or enable it from **Model Catalogue → Engines**.)
+
+2. **Accept the license in-app**
+   ([#1306](https://github.com/debpalash/VoiceStudio/issues/1306)). The code
+   is MIT and the weights are CC-BY-4.0, but the weights are **gated on
+   HuggingFace** behind an access agreement with an acceptable-use clause.
+   VoiceStudio surfaces this before first use: the engine stays unavailable
+   until you review and accept in **Model Catalogue → Engines → PocketTTS**.
+   You also need HuggingFace access to the gated repo (see
+   [downloading-models.md](../downloading-models.md) for token setup).
+
+3. Select the engine via **Model Catalogue → Engines** or
+   `OMNIVOICE_TTS_BACKEND=pockettts`.
+
+## Platform notes
+
+- Works on Linux, Windows, macOS Apple Silicon — CPU only everywhere.
+- **Not available on Intel Macs**: the required PyTorch version has no
+  macOS x86_64 wheel. The engine reports this plainly instead of failing
+  mid-install.
+
+## Behaviour notes
+
+- Output is 24 kHz mono.
+- Six languages, one model per language, chosen by the `language` you
+  request; cloning takes a short reference clip.
+- Runs in a crash-isolated sidecar process (parent Python environment): a
+  wedged generation is hard-killed by a watchdog and its memory reclaimed —
+  something an in-process engine cannot do.
+- The first use downloads the gated weights; the sidecar heartbeats
+  progress during the download so the watchdog doesn't fire.
+
+| Variable | Default | Meaning |
+| --- | --- | --- |
+| `OMNIVOICE_POCKETTTS_RECV_TIMEOUT_S` | `600` | Sidecar response deadline in seconds (min 30; cold loads download weights) |
+
+## Known limits
+
+- No voice design, no emotion controls
+  (see [expressive-speech.md](../expressive-speech.md)).
+- Six languages only — for broader coverage use
+  [OmniVoice](omnivoice.md) ([languages.md](../languages.md)).
+- Revoking the license acceptance takes effect immediately, without a
+  restart — subsequent generations refuse.
+
+## Troubleshooting
+
+- "pocket_tts package not installed": run the `uv sync` above.
+- "license not accepted": open **Model Catalogue → Engines → PocketTTS**
+  and review/accept.
+- Timeouts on a slow connection: raise
+  `OMNIVOICE_POCKETTTS_RECV_TIMEOUT_S` for the first (download-heavy) run.
+- Other issues: [install/troubleshooting.md](../install/troubleshooting.md).
+
+See also: [benchmarks.md](../benchmarks.md),
+[performance.md](../performance.md), [disk usage](disk-usage.md).
diff --git a/docs/engines/pytorch-whisper.md b/docs/engines/pytorch-whisper.md
new file mode 100644
index 00000000..7623911d
--- /dev/null
+++ b/docs/engines/pytorch-whisper.md
@@ -0,0 +1,61 @@
+# VoiceStudio — PyTorch Whisper Engine
+
+Whisper through the plain `transformers` pipeline, riding torch itself. No
+extra install — transformers ships with the app — and because it runs on
+torch's own stack (including torch's bundled cuDNN 9), it works on machines
+where the CTranslate2 engines can't load. It is also the engine that
+genuinely uses **AMD ROCm** GPUs, so auto-detect picks it on ROCm hosts
+([#1529](https://github.com/debpalash/VoiceStudio/issues/1529)).
+
+## Selecting it
+
+- **Model Catalogue → Engines**, ASR tab → **Use** on the PyTorch Whisper
+  row, or `OMNIVOICE_ASR_BACKEND=pytorch-whisper`.
+- Auto-detect picks it on ROCm, and as the last resort everywhere else.
+
+## Best at
+
+- **ROCm dubbing/transcription** — the only Whisper engine that uses the HIP
+  GPU (CTranslate2 has no HIP build, MLX is Apple-only).
+- **Rescue engine** when whisperx/faster-whisper can't load — e.g. the
+  missing-cuDNN-8 case
+  ([#255](https://github.com/debpalash/VoiceStudio/issues/255)) — since it
+  needs neither CTranslate2 nor cuDNN 8.
+
+For lip-sync-grade word timing prefer [whisperx](whisperx.md) or
+[mlx-whisper](mlx-whisper.md); this engine returns the pipeline's own word
+timestamps.
+
+## Platform support
+
+CUDA, Apple Silicon (MPS), ROCm (HIP), and CPU — wherever torch runs, on
+macOS, Windows, and Linux.
+
+## Model selection
+
+`OMNIVOICE_PYTORCH_ASR_MODEL` — default `openai/whisper-large-v3-turbo`. Any
+transformers-format Whisper repo works. Weights download on first load — see
+[downloading-models](../downloading-models.md).
+
+## VRAM preflight
+
+whisper-large-v3-turbo needs roughly 3.2 GiB before generation adds its
+workspace; loading it onto a nearly-full card "succeeds" and then the first
+transcribe OOMs with zero segments. So on CUDA the engine checks free VRAM
+against a 5 GB budget before loading and uses the CPU instead when the card
+is too full (flush the TTS model to restore GPU-speed ASR). Disable with
+`OMNIVOICE_ASR_VRAM_PREFLIGHT=0`.
+
+## Quirks
+
+- If the pipeline fails to import (`AutoFeatureExtractor` errors), the cause
+  is either an incomplete transformers install or a torch/torchvision
+  version mismatch — the error message names the exact reinstall command;
+  the trio has to move together at the pinned versions
+  ([#549](https://github.com/debpalash/VoiceStudio/issues/549),
+  [#1376](https://github.com/debpalash/VoiceStudio/issues/1376)).
+- Transcribes are time-bounded like every local engine:
+  `OMNIVOICE_TRANSCRIBE_CHUNK_TIMEOUT_S` (default 120 s per dub chunk),
+  `OMNIVOICE_ASR_TRANSCRIBE_TIMEOUT_S` (default 300 s whole-file).
+
+Speed comparisons across engines live in [performance](../performance.md).
diff --git a/docs/engines/sherpa-onnx-asr.md b/docs/engines/sherpa-onnx-asr.md
new file mode 100644
index 00000000..765f5553
--- /dev/null
+++ b/docs/engines/sherpa-onnx-asr.md
@@ -0,0 +1,71 @@
+# VoiceStudio — Sherpa-ONNX Dictation Engine
+
+The k2-fsa/sherpa-onnx ONNX runtime as a **live dictation** engine: small
+int8 models that transcribe faster than realtime on CPU, with identical
+behavior on macOS (arm64 + x86_64), Windows, and Linux — no CUDA dependency.
+Streaming models emit partial text frame-by-frame as you speak; offline
+models re-transcribe a growing buffer on a short cadence, so you see live
+partials either way.
+
+## Selecting it
+
+- Ensure `sherpa-onnx` is installed (`uv add sherpa-onnx` on source installs).
+- Pick a dictation model in the app (Model Catalogue → Models lists the
+  curated set below), or **Model Catalogue → Engines**, ASR tab → **Use**, or
+  pin `OMNIVOICE_ASR_BACKEND=sherpa-onnx-asr`.
+- `OMNIVOICE_SHERPA_ASR_MODEL` selects the model — default
+  `sherpa-parakeet-tdt-v3`.
+
+## Best at
+
+- **Live dictation on CPU** — the whole point of this engine. Fast partials,
+  automatic endpointing on silence, no GPU required.
+- It also honors the regular offline `transcribe` contract, so any of its
+  models can transcribe a file — plain text, single segment, no word
+  timestamps, which makes it a dictation/notes tool rather than a dubbing
+  engine.
+
+## The 7 curated models
+
+| Id | Type | Languages | Download |
+| --- | --- | --- | --- |
+| `sherpa-parakeet-tdt-v3` (default) | offline | 25 European languages | 0.67 GB |
+| `sherpa-parakeet-tdt-v2` | offline | English | 0.66 GB |
+| `sherpa-zipformer-bilingual-zh-en` | streaming | Chinese + English | 0.20 GB |
+| `sherpa-paraformer-bilingual-zh-en` | streaming | Chinese + English | 0.24 GB |
+| `sherpa-zipformer-en-20m` | streaming | English | 0.044 GB |
+| `sherpa-zipformer-zh-14m` | streaming | Chinese | 0.025 GB |
+| `sherpa-whisper-tiny` | offline | 90+ languages (auto-detect) | 0.104 GB |
+
+Sizes are measured on-disk download sizes. Weights are int8 ONNX checkpoints
+that download on first use through the same HF cache as everything else —
+see [downloading-models](../downloading-models.md). Peak RAM for the 0.6B
+Parakeets is noticeably higher than their download size (onnxruntime's arena
+allocator holds onto freed blocks).
+
+## Platform support
+
+CPU on every platform, by the strict cross-platform default-parity rule.
+`OMNIVOICE_SHERPA_ASR_PROVIDER` can override the ONNX provider on a verified
+GPU build, but the default never diverges.
+
+## Tuning
+
+- `OMNIVOICE_SHERPA_ASR_THREADS` — decode threads (default 2; the 0.6B
+  Parakeets automatically use up to 4 when the host has the cores, so decode
+  keeps ahead of the speaker).
+- `OMNIVOICE_DICTATION_ENDPOINT_R1` / `OMNIVOICE_DICTATION_ENDPOINT_R2` —
+  streaming endpoint rules in seconds (defaults 1.0 / 0.6: text commits
+  ~0.6 s after you stop speaking). Applied without a restart.
+
+## Quirks
+
+- The recognizer is **pre-warmed in the background** so the first dictation
+  session doesn't pay the 1.3–2.5 s ONNX session load
+  ([#888](https://github.com/debpalash/VoiceStudio/issues/888)); it's then
+  shared warm across sessions.
+- On Apple Silicon, installing the [parakeet-mlx](parakeet-mlx.md) model
+  makes dictation prefer the GPU Parakeet automatically for the 25 covered
+  languages; an explicitly selected sherpa model still wins.
+- The offline `transcribe` path reports `language: auto` — per-file language
+  detection is only meaningful for the Whisper Tiny model.
diff --git a/docs/engines/sherpa-onnx.md b/docs/engines/sherpa-onnx.md
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+# VoiceStudio — Sherpa-ONNX Engine
+
+Sherpa-ONNX (k2-fsa/sherpa-onnx) is a unified C++ ONNX runtime that wraps
+20+ TTS model families (VITS, MeloTTS, Piper, Kokoro, Matcha, and more)
+behind one API, with pre-built wheels for Linux, Windows, and macOS (x86 and
+ARM). You bring the model: point VoiceStudio at any downloaded sherpa-onnx
+TTS model directory.
+
+## When to pick it
+
+- You want a specific community model (e.g. a Piper or VITS voice for your
+  language) that no other engine hosts.
+- You need a dependable CPU engine with optional CUDA acceleration.
+
+## Setup
+
+1. Install the runtime:
+
+   ```bash
+   pip install sherpa-onnx
+   ```
+
+2. Download a TTS model from the
+   [sherpa-onnx releases](https://github.com/k2-fsa/sherpa-onnx/releases)
+   and unpack it somewhere permanent.
+
+3. Point VoiceStudio at the model directory and restart:
+
+   ```bash
+   export OMNIVOICE_SHERPA_MODEL=/path/to/model-dir
+   ```
+
+4. Select the engine via **Model Catalogue → Engines** or
+   `OMNIVOICE_TTS_BACKEND=sherpa-onnx`.
+
+The directory must contain `model.onnx` and `tokens.txt`. Sherpa-ONNX ships
+no bundled default model, so the engine reports unavailable — with the
+reason — until `OMNIVOICE_SHERPA_MODEL` points at a valid directory. (Before
+this gate, selecting the engine unconfigured produced a failure mislabeled
+as out-of-memory —
+[#919](https://github.com/debpalash/VoiceStudio/issues/919).)
+
+## Configuration
+
+| Variable | Default | Meaning |
+| --- | --- | --- |
+| `OMNIVOICE_SHERPA_MODEL` | (unset) | Directory containing `model.onnx` + `tokens.txt` |
+
+## Behaviour notes
+
+- Output defaults to 22.05 kHz (the VITS default); once a model is loaded,
+  its own sample rate is used.
+- CPU is the universal baseline; the CUDA onnxruntime provider is available
+  on Linux/Windows installs.
+- **No cloning**: voices come from the model itself. Multi-speaker VITS
+  models select a voice by numeric speaker id; speed is supported.
+- Languages depend entirely on the model you download.
+
+## Known limits
+
+- One model at a time — switching models means changing
+  `OMNIVOICE_SHERPA_MODEL` and restarting.
+- No voice design, no reference-audio cloning, no emotion controls
+  (see [expressive-speech.md](../expressive-speech.md)).
+
+## Troubleshooting
+
+- "OMNIVOICE_SHERPA_MODEL not set" / "No model.onnx in …": follow Setup
+  above — the variable must point at the *unpacked* model directory, not
+  the archive.
+- Other issues: [install/troubleshooting.md](../install/troubleshooting.md).
+
+See also: [benchmarks.md](../benchmarks.md),
+[languages.md](../languages.md),
+[disk usage](disk-usage.md).
diff --git a/docs/engines/supertonic3.md b/docs/engines/supertonic3.md
new file mode 100644
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+++ b/docs/engines/supertonic3.md
@@ -0,0 +1,76 @@
+# VoiceStudio — Supertonic-3 Engine
+
+Supertonic-3 (Supertone Inc.) is a ~99M-parameter ONNX TTS engine covering
+31 languages with 7 preset voices at native 44.1 kHz. It is CPU-only by
+design — pure ONNX Runtime on the CPU execution provider, with no CUDA or
+MPS path in the upstream SDK — and runs in its own sidecar process so
+crashes and cold init never block the rest of VoiceStudio.
+
+## When to pick it
+
+- Broad language coverage on machines with no usable GPU.
+- Preset-voice narration at a higher sample rate than the default engine.
+
+## Setup
+
+1. Install the optional dependency into VoiceStudio's environment:
+
+   ```bash
+   uv sync --extra supertonic
+   ```
+
+   (Or enable it from **Model Catalogue → Engines**, which installs the
+   pinned `supertonic` wheel for you.)
+
+2. **Accept the license in-app.** First use is gated behind an explicit
+   acceptance dialog: the inference SDK is MIT, but the model weights are
+   **OpenRAIL-M**, which carries use restrictions. The engine stays
+   unavailable until you review and accept in **Model Catalogue → Engines →
+   Supertonic-3**.
+
+3. Select the engine via **Model Catalogue → Engines** or
+   `OMNIVOICE_TTS_BACKEND=supertonic3`.
+
+The first synthesis cold-downloads ~400 MB of model weights, pinned to an
+exact HuggingFace revision SHA so the bytes match what the SDK was validated
+against. See [downloading-models.md](../downloading-models.md).
+
+## Voices
+
+Seven preset voices are surfaced: `M1` (default), `M3`, `M4`, `M5`, `F3`,
+`F4`, `F5`. The SDK itself accepts the full `M1`–`M5` / `F1`–`F5` set if a
+caller passes one explicitly; unknown ids fall back to the default with a
+log line.
+
+## Behaviour notes
+
+- Output is 44.1 kHz mono.
+- Runs as a long-lived sidecar in the parent Python environment (its
+  dependencies — onnxruntime, numpy, soundfile — already match
+  VoiceStudio's pins); subsequent calls reuse the warm ONNX session.
+- `speed` is clamped to 0.7–2.0; quality steps clamp to 5–12.
+- Language is an ISO 639-1 code; Auto engages the SDK's multilingual
+  fallback.
+
+## Known limits
+
+- **No cloning and no voice design** — preset voices only. Dub/batch jobs
+  that need cloning won't select it.
+- CPU-only: hardware acceleration is a property of the upstream SDK, not a
+  VoiceStudio limitation.
+- OpenRAIL-M weights are not covered by VoiceStudio's blanket
+  commercial-use statement — review the model license terms in the
+  acceptance dialog.
+
+## Troubleshooting
+
+- "supertonic package not installed": run the `uv sync` above or enable
+  from the Model Catalogue.
+- "license not accepted": open **Model Catalogue → Engines → Supertonic-3**
+  and accept.
+- Other issues: [install/troubleshooting.md](../install/troubleshooting.md).
+
+See also: [benchmarks.md](../benchmarks.md),
+[languages.md](../languages.md),
+[expressive-speech.md](../expressive-speech.md),
+[disk usage](disk-usage.md).
diff --git a/docs/engines/voxcpm2.md b/docs/engines/voxcpm2.md
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+++ b/docs/engines/voxcpm2.md
@@ -0,0 +1,76 @@
+# VoiceStudio — VoxCPM2 Engine
+
+VoxCPM2 (OpenBMB) is the studio-quality option: native 48 kHz output,
+zero-shot voice cloning, and — uniquely among VoiceStudio's engines —
+**voice design**: creating a synthetic voice from a text description
+("young female, warm tone, British accent") with no reference audio at all.
+
+## When to pick it
+
+- You want voice design without a reference clip.
+- You want the highest output sample rate (48 kHz vs OmniVoice's 24 kHz).
+- Your language is among its 30 supported languages: Arabic, Burmese,
+  Chinese, Danish, Dutch, English, Finnish, French, German, Greek, Hebrew,
+  Hindi, Indonesian, Italian, Japanese, Khmer, Korean, Lao, Malay,
+  Norwegian, Polish, Portuguese, Russian, Spanish, Swahili, Swedish,
+  Tagalog, Thai, Turkish, Vietnamese.
+
+## Requirements
+
+- Python ≥ 3.10, PyTorch ≥ 2.5.
+- CUDA ≥ 12 recommended for full speed; MPS (Apple Silicon) and CPU also
+  work.
+
+## Setup
+
+Install the package into VoiceStudio's Python environment:
+
+```bash
+pip install "voxcpm>=2.0.3"
+```
+
+That is a version **floor**, not a pin — an older install still works, but
+the engine logs an upgrade hint at load time. Then select the engine via
+**Model Catalogue → Engines** or `OMNIVOICE_TTS_BACKEND=voxcpm2`.
+
+## Model selection
+
+| Variable | Default | Meaning |
+| --- | --- | --- |
+| `OMNIVOICE_VOXCPM_MODEL` | `openbmb/VoxCPM2` | HuggingFace checkpoint to load |
+
+The first use downloads a multi-GB checkpoint from HuggingFace. A download
+interrupted near the end used to abort the load outright
+([#1224](https://github.com/debpalash/VoiceStudio/issues/1224)); the load is
+now retried once with a fresh client. See
+[downloading-models.md](../downloading-models.md).
+
+## Behaviour notes
+
+- **Voice design:** provide a description and no reference audio.
+- **Cloning:** the reference clip is prepared before use (edge-silence trim
+  and length cap) so dead air in a raw clip doesn't condition the output; on
+  any prep problem the raw clip is used as-is.
+- **Style instructions** are passed as an inline prefix to the text.
+- VoxCPM2 emits mastered, studio-grade audio, so VoiceStudio **skips its
+  shared mastering chain** (which is tuned for 24 kHz engines) — only benign
+  loudness normalization applies.
+- A trailing-silence guard trims long near-silent tails from generations,
+  keeping a short natural tail.
+
+## Known limits
+
+- Slower than the lightweight CPU engines — see
+  [benchmarks.md](../benchmarks.md) and [performance.md](../performance.md).
+- Language coverage is 30 languages; for anything else use the default
+  [OmniVoice](omnivoice.md) engine ([languages.md](../languages.md)).
+
+## Troubleshooting
+
+- Engine shows unavailable: the `voxcpm` package isn't installed — run the
+  `pip install` above and restart VoiceStudio.
+- Repeated first-download failures: check connectivity/HF access, then see
+  [install/troubleshooting.md](../install/troubleshooting.md).
+
+See also: [expressive-speech.md](../expressive-speech.md),
+[disk usage](disk-usage.md).
diff --git a/docs/engines/whisperx.md b/docs/engines/whisperx.md
new file mode 100644
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+++ b/docs/engines/whisperx.md
@@ -0,0 +1,80 @@
+# VoiceStudio — WhisperX Engine
+
+WhisperX is the default ASR engine on CUDA and plain-CPU hosts: faster-whisper
+(CTranslate2) transcription plus a **wav2vec2 forced-alignment** pass that
+snaps word boundaries to ±10–30 ms (Whisper's own timestamps are ±100–300 ms).
+That word timing is what dubbing lip-sync depends on, which is why auto-detect
+prefers it wherever CTranslate2 can use the GPU.
+
+## Selecting it
+
+- **Model Catalogue → Engines**, ASR tab → **Use** on the WhisperX row, or
+- pin it with `OMNIVOICE_ASR_BACKEND=whisperx` (the env var always wins over
+  the Settings pick; with neither set, auto-detect chooses per-hardware).
+
+## Best at
+
+- **Dubbing** — the forced alignment is the accuracy tier lip-sync needs.
+- **Batch transcription** with word-level subtitles.
+- Multi-speaker work: it pairs with pyannote speaker diarization — see
+  [diarization](../features/diarization.md).
+
+## Platform support
+
+| Host | What happens |
+| --- | --- |
+| NVIDIA CUDA | GPU, float16 (degrades automatically, see below) |
+| CPU (any OS) | int8 — works, but slow for large-v3 |
+| Apple Silicon | CPU only — CTranslate2 has no Metal build, so auto-detect prefers [mlx-whisper](mlx-whisper.md) there ([#1127](https://github.com/debpalash/VoiceStudio/issues/1127)) |
+| AMD ROCm | CPU only — CTranslate2 has no HIP build, so auto-detect prefers [pytorch-whisper](pytorch-whisper.md) there ([#1529](https://github.com/debpalash/VoiceStudio/issues/1529)) |
+
+## Model selection
+
+- `ASR_MODEL_WHISPERX` — default `large-v3`. Accepts the usual size aliases
+  (`tiny` … `large-v3`, `distil-large-v3`) or a full HF repo id. Weights
+  download on first load — see [downloading-models](../downloading-models.md).
+- `OMNIVOICE_ALIGN_DEVICE` — force the wav2vec2 aligner's device. Aligners
+  exist for ~20 major languages; other languages keep Whisper's native word
+  timestamps instead of failing.
+
+## VRAM preflight and degradation
+
+Loading fp16 large-v3 onto a nearly-full 8 GB card dies as a *native* CUDA
+abort — no Python exception, the whole backend goes down
+([#723](https://github.com/debpalash/VoiceStudio/issues/723)). So before every
+load the engine checks free VRAM against per-compute-type budgets
+(float16 5.0 GB, int8_float16 3.5 GB, int8 3.0 GB, scaled down for smaller
+models) and degrades the compute type — or falls to CPU int8 — instead of
+starting a load that would kill the process. Disable with
+`OMNIVOICE_ASR_VRAM_PREFLIGHT=0`.
+
+Two more fallback chains run at load time:
+
+- GPUs without efficient fp16 (older Maxwell/Pascal, GTX 16xx) raise a
+  compute-type error — the engine retries int8_float16, then int8
+  ([#551](https://github.com/debpalash/VoiceStudio/issues/551)).
+- A genuine CUDA OOM retries on CPU int8, so dubbing still completes
+  (slower, same model and accuracy).
+
+## Quirks
+
+- **cuDNN 8 required on CUDA.** CTranslate2 links cuDNN 8; if it's missing the
+  process fast-fails with no traceback, so the engine is reported unavailable
+  up front and selection falls through to pytorch-whisper, which uses torch's
+  own cuDNN 9 ([#1371](https://github.com/debpalash/VoiceStudio/issues/1371)).
+- On some hardened Linux kernels CTranslate2's native library is rejected with
+  "cannot enable executable stack" — reported as unavailable, not a crash
+  ([#692](https://github.com/debpalash/VoiceStudio/issues/692)).
+- A partially-installed environment (interrupted sync, antivirus quarantine)
+  can break WhisperX's deep import chain (whisperx → pyannote →
+  lightning_fabric). The engine is then reported unavailable with a repair
+  hint — reinstall, or `uv sync --reinstall` on a source checkout
+  ([#1185](https://github.com/debpalash/VoiceStudio/issues/1185)).
+- Audio is decoded through VoiceStudio's validated ffmpeg, not a bare `ffmpeg`
+  PATH lookup ([#479](https://github.com/debpalash/VoiceStudio/issues/479)).
+- Transcribes are time-bounded: each dub chunk by
+  `OMNIVOICE_TRANSCRIBE_CHUNK_TIMEOUT_S` (default 120 s), whole files by
+  `OMNIVOICE_ASR_TRANSCRIBE_TIMEOUT_S` (default 300 s). Raise them for very
+  long files on slow hardware.
+
+Speed comparisons across engines live in [performance](../performance.md).