fix: add alpha channel input for Qwen Image 2.1 and relative docs (#2021)

docs/backend.md

@@ -156,8 +156,11 @@ the runner's graph-cut capacity checks.
 
 Runtime capacity checks also leave 512 MiB of currently free device memory for
 backend scratch buffers and pipelines, including with explicit backend assignments.
-They cap stale free-memory reports by the device's total memory minus tracked
-resident allocations and reject reports that exceed the device's total memory.
+They cap free-memory reports by the device's total memory minus tracked
+resident allocations. Vulkan reports exceeding total memory are rejected because
+its heap-budget subtraction can underflow. Other backends use the cap instead of
+treating such reports as zero free memory. Failed checks log the reported free and
+total memory alongside tracked weight and runtime allocations.
 
 Components are considered in `diffusion`, `te`, `vae` order so that repeatedly
 used diffusion weights have priority. Each component's weights use the first

docs/qwen_image_2.1.md

@@ -39,3 +39,21 @@ Pass the reference image with `-r` and describe the edit in `-p`. Vision weights
 ```
 
 For multiple reference images, repeat `-r` in the desired order, for example `-r first.png -r second.png`.
+
+### Alpha channel
+
+This model supports alpha channel output. As the model determines whether to output a regular image or with transparency through the prompt, according to [official recommendation](https://github.com/QwenLM/Qwen-Image-2.1#transparent-image-generation-rgba), use the following prompt format for better results:
+
+> `This is an RGBA image with transparency. <your description>. The image has alpha channel and the background is transparent.`
+
+Since transparency is decided by the prompt rather than by the input or an explicit switch, the same format applies equally to editing, whether or not the reference image itself has an alpha channel. Note that alpha is kept only in `.png` and `.webp` outputs; saving as `.jpg` drops the transparency.
+
+Here are some examples ran with Q6_K quantization:
+| Input | Prompt | Output |
+| --- | --- | --- |
+| ![Qwen Image 2.1 alpha input example 1](../assets/qwen/qwen-image-2.1-alpha-in1.png) | This is an RGBA image with transparency. Replace the text "BLOOM" with "Qwen Image 2.1", keeping the same font of the original text. The image has alpha channel and the background is transparent. | ![Qwen Image 2.1 alpha output example 1](../assets/qwen/qwen-image-2.1-alpha-out1.png) |
+| ![Qwen Image 2.1 alpha input example 2](../assets/logo.png) | This is an RGBA image with transparency. Remove the background of the image, keeping only the text and cat. The image has alpha channel and the background is transparent. | ![Qwen Image 2.1 alpha output example 2](../assets/qwen/qwen-image-2.1-alpha-out2.png) |
+
+### Other features
+
+Other features of the model could be found on the [model card from QwenLM/Qwen-Image-2.1 repo](https://github.com/QwenLM/Qwen-Image-2.1), including 2 finetuned prompt rewriting Qwen3.5-9B model.

examples/cli/main.cpp

@@ -357,7 +357,8 @@ bool load_images_from_dir(const std::string dir,
             LOG_VERBOSE("load image %zu from '%s'", images.size(), path.c_str());
             int width             = 0;
             int height            = 0;
-            uint8_t* image_buffer = load_image_from_file(path.c_str(), width, height, expected_width, expected_height);
+            int loaded_channel    = 0;
+            uint8_t* image_buffer = load_image_from_file(path.c_str(), width, height, loaded_channel, expected_width, expected_height);
             if (image_buffer == nullptr) {
                 LOG_ERROR("load image from '%s' failed", path.c_str());
                 return false;
@@ -365,7 +366,7 @@ bool load_images_from_dir(const std::string dir,
 
             images.emplace_back(sd_image_t{(uint32_t)width,
                                            (uint32_t)height,
-                                           3,
+                                           (uint32_t)loaded_channel,
                                            image_buffer});
 
             if (max_image_num > 0 && static_cast<int>(images.size()) >= max_image_num) {
@@ -781,7 +782,8 @@ int main(int argc, const char* argv[]) {
     };
 
     if (gen_params.init_image_path.size() > 0) {
-        if (!load_image_and_update_size(gen_params.init_image_path, gen_params.init_image)) {
+        const bool native_init = cli_params.mode == IMG_GEN || cli_params.mode == ADETAILER;
+        if (!load_image_and_update_size(gen_params.init_image_path, gen_params.init_image, true, native_init ? 0 : 3)) {
             return 1;
         }
     }
@@ -795,8 +797,8 @@ int main(int argc, const char* argv[]) {
     if (gen_params.ref_image_paths.size() > 0) {
         gen_params.ref_images.clear();
         for (auto& path : gen_params.ref_image_paths) {
-            SDImageOwner ref_image({0, 0, 3, nullptr});
-            if (!load_image_and_update_size(path, ref_image, false)) {
+            SDImageOwner ref_image({0, 0, 0, nullptr});
+            if (!load_image_and_update_size(path, ref_image, false, 0)) {
                 return 1;
             }
             gen_params.ref_images.push_back(std::move(ref_image));

examples/common/common.cpp

@@ -1754,7 +1754,7 @@ ArgOptions SDGenerationParams::get_options() {
          on_scm_policy_arg},
         {"",
          "--vae-tile-size",
-         "tile size for vae tiling, format [X]x[Y] (default: 32x32)",
+         "tile size for vae tiling in latent units, not image pixels, format [X]x[Y] (default: 32x32)",
          on_tile_size_arg},
         {"",
          "--vae-relative-tile-size",
@@ -1848,20 +1848,22 @@ bool decode_base64_image(const std::string& encoded_input,
         return false;
     }
 
-    int decoded_width  = 0;
-    int decoded_height = 0;
-    uint8_t* raw_data  = load_image_from_memory(reinterpret_cast<const char*>(image_bytes.data()),
-                                                static_cast<int>(image_bytes.size()),
-                                                decoded_width,
-                                                decoded_height,
-                                                expected_width,
-                                                expected_height,
-                                                target_channels);
+    int decoded_width    = 0;
+    int decoded_height   = 0;
+    int resolved_channel = target_channels;
+    uint8_t* raw_data    = load_image_from_memory(reinterpret_cast<const char*>(image_bytes.data()),
+                                                  static_cast<int>(image_bytes.size()),
+                                                  decoded_width,
+                                                  decoded_height,
+                                                  resolved_channel,
+                                                  expected_width,
+                                                  expected_height,
+                                                  target_channels);
     if (raw_data == nullptr) {
         return false;
     }
 
-    out_image.reset({(uint32_t)decoded_width, (uint32_t)decoded_height, (uint32_t)target_channels, raw_data});
+    out_image.reset({(uint32_t)decoded_width, (uint32_t)decoded_height, (uint32_t)resolved_channel, raw_data});
     return true;
 }
 
@@ -2215,7 +2217,7 @@ bool SDGenerationParams::from_json_str(
         LOG_ERROR("invalid lora");
         return false;
     }
-    if (!parse_image_json_field(j, "init_image", 3, width, height, init_image)) {
+    if (!parse_image_json_field(j, "init_image", 0, width, height, init_image)) {
         LOG_ERROR("invalid init_image");
         return false;
     }
@@ -2223,7 +2225,12 @@ bool SDGenerationParams::from_json_str(
         LOG_ERROR("invalid end_image");
         return false;
     }
-    if (!parse_image_array_json_field(j, "ref_images", 3, width, height, ref_images)) {
+    if (!parse_image_array_json_field(j,
+                                      "ref_images",
+                                      0,
+                                      auto_resize_ref_image ? width : 0,
+                                      auto_resize_ref_image ? height : 0,
+                                      ref_images)) {
         LOG_ERROR("invalid ref_images");
         return false;
     }

examples/common/media_io.cpp

@@ -261,6 +261,10 @@ uint8_t* decode_webp_image_to_buffer(const uint8_t* data,
     height               = features.height;
     source_channel_count = features.has_alpha ? 4 : 3;
 
+    if (expected_channel == 0) {
+        expected_channel = source_channel_count;
+    }
+
     const size_t pixel_count = static_cast<size_t>(width) * static_cast<size_t>(height);
 
     if (expected_channel == 1) {
@@ -481,7 +485,8 @@ uint8_t* load_image_common(bool from_memory,
                            int& height,
                            int expected_width,
                            int expected_height,
-                           int expected_channel) {
+                           int expected_channel,
+                           int& out_channel) {
     const char* image_path;
     FreeUniquePtr<uint8_t> image_buffer;
     int source_channel_count = 0;
@@ -538,6 +543,32 @@ uint8_t* load_image_common(bool from_memory,
         LOG_ERROR("load image from '%s' failed", image_path);
         return nullptr;
     }
+    if (expected_channel == 0) {
+        expected_channel = source_channel_count == 2 ? 4 : (source_channel_count == 1 ? 3 : source_channel_count);
+        if (expected_channel != source_channel_count) {
+            FreeUniquePtr<uint8_t> promoted((uint8_t*)malloc((size_t)width * height * expected_channel));
+            if (promoted == nullptr) {
+                LOG_ERROR("error: allocate memory for channel promotion, image_path = %s", image_path);
+                return nullptr;
+            }
+            const size_t pixel_count = (size_t)width * (size_t)height;
+            for (size_t i = 0; i < pixel_count; ++i) {
+                if (source_channel_count == 1) {
+                    promoted.get()[i * 3 + 0] = image_buffer.get()[i];
+                    promoted.get()[i * 3 + 1] = image_buffer.get()[i];
+                    promoted.get()[i * 3 + 2] = image_buffer.get()[i];
+                } else {
+                    promoted.get()[i * 4 + 0] = image_buffer.get()[i * 2];
+                    promoted.get()[i * 4 + 1] = image_buffer.get()[i * 2];
+                    promoted.get()[i * 4 + 2] = image_buffer.get()[i * 2];
+                    promoted.get()[i * 4 + 3] = image_buffer.get()[i * 2 + 1];
+                }
+            }
+            image_buffer         = std::move(promoted);
+            source_channel_count = expected_channel;
+        }
+    }
+    // stb reports the source channel count even when it converts the output.
     if (source_channel_count < expected_channel) {
         fprintf(stderr,
                 "the number of channels for the input image must be >= %d,"
@@ -597,7 +628,7 @@ uint8_t* load_image_common(bool from_memory,
         }
         stbir_resize(image_buffer.get(), width, height, 0,
                      resized_image_buffer.get(), expected_width, expected_height, 0, STBIR_TYPE_UINT8,
-                     expected_channel, STBIR_ALPHA_CHANNEL_NONE, 0,
+                     expected_channel, expected_channel == 4 ? 3 : STBIR_ALPHA_CHANNEL_NONE, 0,
                      STBIR_EDGE_CLAMP, STBIR_EDGE_CLAMP,
                      STBIR_FILTER_BOX, STBIR_FILTER_BOX,
                      STBIR_COLORSPACE_SRGB, nullptr);
@@ -605,6 +636,7 @@ uint8_t* load_image_common(bool from_memory,
         height       = expected_height;
         image_buffer = std::move(resized_image_buffer);
     }
+    out_channel = expected_channel;
     return image_buffer.release();
 }
 
@@ -777,10 +809,11 @@ bool write_image_to_file(const std::string& path,
 uint8_t* load_image_from_file(const char* image_path,
                               int& width,
                               int& height,
+                              int& out_channel,
                               int expected_width,
                               int expected_height,
                               int expected_channel) {
-    return load_image_common(false, image_path, 0, width, height, expected_width, expected_height, expected_channel);
+    return load_image_common(false, image_path, 0, width, height, expected_width, expected_height, expected_channel, out_channel);
 }
 
 bool load_sd_image_from_file(sd_image_t* image,
@@ -790,13 +823,14 @@ bool load_sd_image_from_file(sd_image_t* image,
                              int expected_channel) {
     int width;
     int height;
-    image->data = load_image_common(false, image_path, 0, width, height, expected_width, expected_height, expected_channel);
+    int resolved_channel = expected_channel;
+    image->data          = load_image_common(false, image_path, 0, width, height, expected_width, expected_height, expected_channel, resolved_channel);
     if (image->data == nullptr) {
         return false;
     }
     image->width   = width;
     image->height  = height;
-    image->channel = expected_channel;
+    image->channel = resolved_channel;
     return true;
 }
 
@@ -804,10 +838,11 @@ uint8_t* load_image_from_memory(const char* image_bytes,
                                 int len,
                                 int& width,
                                 int& height,
+                                int& out_channel,
                                 int expected_width,
                                 int expected_height,
                                 int expected_channel) {
-    return load_image_common(true, image_bytes, len, width, height, expected_width, expected_height, expected_channel);
+    return load_image_common(true, image_bytes, len, width, height, expected_width, expected_height, expected_channel, out_channel);
 }
 
 static void append_avi_metadata(std::vector<uint8_t>& data, const std::string& parameters) {

examples/common/media_io.h

@@ -32,9 +32,12 @@ bool write_image_to_file(const std::string& path,
                          const std::string& parameters = "",
                          int quality                   = 90);
 
+// expected_channel == 0 preserves native channels (grayscale -> RGB, gray+alpha -> RGBA).
+// out_channel receives the output channel count.
 uint8_t* load_image_from_file(const char* image_path,
                               int& width,
                               int& height,
+                              int& out_channel,
                               int expected_width   = 0,
                               int expected_height  = 0,
                               int expected_channel = 3);
@@ -49,6 +52,7 @@ uint8_t* load_image_from_memory(const char* image_bytes,
                                 int len,
                                 int& width,
                                 int& height,
+                                int& out_channel,
                                 int expected_width   = 0,
                                 int expected_height  = 0,
                                 int expected_channel = 3);

examples/server/api.md

@@ -735,12 +735,15 @@ Any image field accepts:
 
 Channel expectations:
 
-- `init_image`: 3 channels
-- `ref_images[]`: 3 channels
+- `init_image`: native channels (3 or 4); alpha is preserved and applied per model
+- `ref_images[]`: native channels (3 or 4); alpha is preserved and applied per model
 - `control_image`: 3 channels
 - `ip_adapter_image`: 3 channels
 - `mask_image`: 1 channel
 
+Models that support RGBA (e.g. Qwen-Image 2.1) use the alpha channel of `init_image`
+and `ref_images[]`. RGB-only models drop it, so sending RGBA is safe for every model.
+
 If omitted or null:
 
 - single-image fields map to an empty `sd_image_t`

examples/server/routes_openai.cpp

@@ -158,24 +158,44 @@ static bool build_openai_edit_request(const httplib::Request& req,
     request.gen_params.batch_count = n;
 
     for (auto& bytes : images_bytes) {
-        int img_w           = 0;
-        int img_h           = 0;
-        uint8_t* raw_pixels = load_image_from_memory(
-            reinterpret_cast<const char*>(bytes.data()),
-            static_cast<int>(bytes.size()),
-            img_w, img_h,
-            width, height, 3);
+        int img_w            = 0;
+        int img_h            = 0;
+        int resolved_channel = 0;
+        uint8_t* raw_pixels  = load_image_from_memory(
+             reinterpret_cast<const char*>(bytes.data()),
+             static_cast<int>(bytes.size()),
+             img_w, img_h, resolved_channel,
+             0, 0, 0);
         if (raw_pixels == nullptr) {
             continue;
         }
 
-        SDImageOwner image_owner({(uint32_t)img_w, (uint32_t)img_h, 3, raw_pixels});
+        const bool is_first_ref_image = request.gen_params.ref_images.empty();
+        SDImageOwner image_owner({(uint32_t)img_w, (uint32_t)img_h, (uint32_t)resolved_channel, raw_pixels});
         request.gen_params.set_width_and_height_if_unset(image_owner.get().width, image_owner.get().height);
-        request.gen_params.ref_images.push_back(std::move(image_owner));
-    }
 
-    if (!request.gen_params.ref_images.empty()) {
-        request.gen_params.init_image = request.gen_params.ref_images.front();
+        if (is_first_ref_image) {
+            int init_w = 0;
+            int init_h = 0;
+            if (request.gen_params.width_and_height_are_set()) {
+                init_w = request.gen_params.width;
+                init_h = request.gen_params.height;
+            }
+
+            int init_img_w            = 0;
+            int init_img_h            = 0;
+            int init_resolved_channel = 0;
+            uint8_t* init_pixels     = load_image_from_memory(
+                 reinterpret_cast<const char*>(bytes.data()),
+                 static_cast<int>(bytes.size()),
+                 init_img_w, init_img_h, init_resolved_channel,
+                 init_w, init_h, 0);
+            if (init_pixels != nullptr) {
+                request.gen_params.init_image.reset({(uint32_t)init_img_w, (uint32_t)init_img_h, (uint32_t)init_resolved_channel, init_pixels});
+            }
+        }
+
+        request.gen_params.ref_images.push_back(std::move(image_owner));
     }
 
     if (!mask_bytes.empty()) {
@@ -185,13 +205,14 @@ static bool build_openai_edit_request(const httplib::Request& req,
             expected_width  = request.gen_params.width;
             expected_height = request.gen_params.height;
         }
-        int mask_w = 0;
-        int mask_h = 0;
+        int mask_w       = 0;
+        int mask_h       = 0;
+        int mask_channel = 0;
 
         uint8_t* mask_raw = load_image_from_memory(
             reinterpret_cast<const char*>(mask_bytes.data()),
             static_cast<int>(mask_bytes.size()),
-            mask_w, mask_h,
+            mask_w, mask_h, mask_channel,
             expected_width, expected_height, 1);
         request.gen_params.mask_image.reset({(uint32_t)mask_w, (uint32_t)mask_h, 1, mask_raw});
         const sd_image_t& mask_image = request.gen_params.mask_image.get();

examples/server/routes_sdapi.cpp

@@ -199,7 +199,7 @@ static bool build_sdapi_img_gen_request(const json& j,
 
         if (j.contains("init_images") && j["init_images"].is_array() && !j["init_images"].empty()) {
             if (decode_base64_image(j["init_images"][0].get<std::string>(),
-                                    3,
+                                    0,
                                     expected_width,
                                     expected_height,
                                     request.gen_params.init_image)) {
@@ -243,9 +243,13 @@ static bool build_sdapi_img_gen_request(const json& j,
             }
             SDImageOwner image_owner;
             if (decode_base64_image(extra_image.get<std::string>(),
-                                    3,
-                                    request.gen_params.width_and_height_are_set() ? request.gen_params.width : 0,
-                                    request.gen_params.width_and_height_are_set() ? request.gen_params.height : 0,
+                                    0,
+                                    request.gen_params.auto_resize_ref_image && request.gen_params.width_and_height_are_set()
+                                        ? request.gen_params.width
+                                        : 0,
+                                    request.gen_params.auto_resize_ref_image && request.gen_params.width_and_height_are_set()
+                                        ? request.gen_params.height
+                                        : 0,
                                     image_owner)) {
                 const sd_image_t& image = image_owner.get();
                 request.gen_params.set_width_and_height_if_unset(image.width, image.height);

src/conditioning/conditioner.hpp

@@ -2219,7 +2219,10 @@ struct LLMEmbedder : public Conditioner {
                                           false,
                                           deepstack_image_embeds,
                                           image_grids);
-        GGML_ASSERT(!hidden_states.empty());
+        if (hidden_states.empty()) {
+            LOG_ERROR("LLM prompt encoding failed");
+            return {};
+        }
         hidden_states = apply_token_weights(std::move(hidden_states), weights);
         GGML_ASSERT(hidden_states.shape()[1] > prompt_template_encode_start_idx);
 

src/core/backend_fit.cpp

@@ -478,7 +478,11 @@ namespace sd::backend_fit {
         return true;
     }
 
-    bool prepare_vae_decode_retry_tiling(sd_tiling_params_t& tiling_params, bool prefer_temporal_tiling) {
+    bool prepare_vae_decode_retry_tiling(sd_tiling_params_t& tiling_params, bool prefer_temporal_tiling, ggml_status status) {
+        // Execution failures can leave the device unusable; tiling only helps with allocation failures.
+        if (status != GGML_STATUS_ALLOC_FAILED) {
+            return false;
+        }
         const char* retry_mode = nullptr;
         if (prefer_temporal_tiling && !tiling_params.temporal_tiling) {
             tiling_params.temporal_tiling = true;
@@ -498,7 +502,7 @@ namespace sd::backend_fit {
             return false;
         }
 
-        LOG_WARN("VAE decode failed (likely out of memory); retrying with %s tiling",
+        LOG_WARN("VAE decode ran out of memory; retrying with %s tiling",
                  retry_mode);
         return true;
     }

src/core/backend_fit.h

@@ -16,7 +16,8 @@ namespace sd::backend_fit {
                               std::string& params_spec);
 
     bool prepare_vae_decode_retry_tiling(sd_tiling_params_t& tiling_params,
-                                         bool prefer_temporal_tiling);
+                                         bool prefer_temporal_tiling,
+                                         ggml_status status);
 
 }  // namespace sd::backend_fit
 

src/core/ggml_runner.cpp

@@ -590,6 +590,7 @@ std::optional<sd::Tensor<float>> GGMLRunner::compute(get_graph_cb_t get_graph,
                                                      bool auto_runner_end,
                                                      bool no_return,
                                                      const std::function<bool()>& read_outputs) {
+    last_compute_status_ = GGML_STATUS_FAILED;
     if (graph_active_) {
         LOG_ERROR("%s does not support reentrant graph execution", get_desc().c_str());
         return std::nullopt;
@@ -613,7 +614,9 @@ std::optional<sd::Tensor<float>> GGMLRunner::compute(get_graph_cb_t get_graph,
         GGMLRunner& runner;
         const bool& success;
         ~GraphEndGuard() {
-            runner.workspace_.segment_end();
+            if (!runner.workspace_.segment_end()) {
+                runner.last_compute_status_ = GGML_STATUS_FAILED;
+            }
             runner.cache_.graph_end(false);
             runner.cut_cache_.clear();
             runner.free_compute_ctx();
@@ -642,6 +645,7 @@ std::optional<sd::Tensor<float>> GGMLRunner::compute(get_graph_cb_t get_graph,
     try {
         output = execute_graph(graph, n_threads, no_return, read_outputs);
     } catch (const std::exception& error) {
+        last_compute_status_ = GGML_STATUS_FAILED;
         LOG_ERROR("%s graph execution failed on %s: %s", get_desc().c_str(),
                   ggml_backend_name(runtime_backend), error.what());
         return std::nullopt;
@@ -649,6 +653,7 @@ std::optional<sd::Tensor<float>> GGMLRunner::compute(get_graph_cb_t get_graph,
     success = output.has_value();
     if (success) {
         cache_.graph_end(true);
+        last_compute_status_ = GGML_STATUS_SUCCESS;
     }
     return output;
 }
@@ -766,6 +771,7 @@ bool GGMLRunner::execute_segment(ggml_cgraph* graph, int n_threads) {
     }
     workspace_.synchronize();
     if (status != GGML_STATUS_SUCCESS) {
+        last_compute_status_ = status;
         LOG_ERROR("%s compute failed: %s", get_desc().c_str(), ggml_status_to_string(status));
         return false;
     }
@@ -818,6 +824,7 @@ std::optional<Tensor<float>> GGMLRunner::execute_graph(ggml_cgraph* graph, int n
     const auto& cached_plan     = resolve_graph_cut_plan(graph);
     const auto full_measurement = measure(graph, cached_plan.compute_buffer_size);
     if (full_measurement.buffers.empty()) {
+        last_compute_status_ = GGML_STATUS_ALLOC_FAILED;
         return std::nullopt;
     }
     auto manager         = residency_manager.lock();
@@ -888,7 +895,9 @@ std::optional<Tensor<float>> GGMLRunner::execute_graph(ggml_cgraph* graph, int n
             SegmentGraphBindings& bindings;
             ggml_context* context;
             ~SegmentCleanup() {
-                runner.workspace_.segment_end();
+                if (!runner.workspace_.segment_end()) {
+                    runner.last_compute_status_ = GGML_STATUS_FAILED;
+                }
                 bindings.restore();
                 weights.segment_end();
                 ggml_free(context);
@@ -898,6 +907,7 @@ std::optional<Tensor<float>> GGMLRunner::execute_graph(ggml_cgraph* graph, int n
 
         auto measurement = segmented ? measure(segment_graph, segment.compute_buffer_size) : full_measurement;
         if (!workspace_.prepare(measurement)) {
+            last_compute_status_ = GGML_STATUS_ALLOC_FAILED;
             return fail_segment("workspace preparation");
         }
         const size_t cut_bytes       = last ? 0 : cut_cache_.estimate_output_bytes(graph, segment);
@@ -912,7 +922,11 @@ std::optional<Tensor<float>> GGMLRunner::execute_graph(ggml_cgraph* graph, int n
                 sync_runtime_residency();
                 requests = memory_requests(measurement.buffers, new_cache_bytes);
             }
-            return weights.ensure_segment_capacity(index, requests);
+            const bool ready = weights.ensure_segment_capacity(index, requests);
+            if (!ready && manager != nullptr) {
+                last_compute_status_ = GGML_STATUS_ALLOC_FAILED;
+            }
+            return ready;
         };
         if (!weights.segment_start(index, ensure_capacity)) {
             return fail_segment("weight preparation");
@@ -921,12 +935,17 @@ std::optional<Tensor<float>> GGMLRunner::execute_graph(ggml_cgraph* graph, int n
         if (!workspace_.measurement_matches(segment_graph, measurement)) {
             measurement = measure(segment_graph, segment.compute_buffer_size);
         }
-        if (!workspace_.prepare(measurement) || !ensure_capacity()) {
+        if (!workspace_.prepare(measurement)) {
+            last_compute_status_ = GGML_STATUS_ALLOC_FAILED;
+            return fail_segment("workspace preparation");
+        }
+        if (!ensure_capacity()) {
             return fail_segment("workspace capacity check");
         }
         if (!workspace_.allocate(segment_graph, [&](ggml_backend_sched_t scheduler, ggml_cgraph* current) {
                 pin_multi_device_nodes(scheduler, current);
             })) {
+            last_compute_status_ = GGML_STATUS_ALLOC_FAILED;
             return fail_segment("workspace allocation");
         }
         for (const auto& size : measurement.buffers) {
@@ -964,6 +983,7 @@ std::optional<Tensor<float>> GGMLRunner::execute_graph(ggml_cgraph* graph, int n
             }
         }
         if (!workspace_.segment_end()) {
+            last_compute_status_ = GGML_STATUS_FAILED;
             return fail_segment("workspace synchronization");
         }
         // Final outputs and their callbacks may still be views of consumed cuts.

src/core/ggml_runner.h

@@ -130,7 +130,8 @@ ggml_tensor* ggml_ext_attention_ext(GGMLRunnerContext* ctx,
 struct GGMLRunner {
 private:
     std::map<ggml_backend_t, size_t> logged_compute_bytes_;
-    size_t logged_segment_count_ = 0;
+    size_t logged_segment_count_     = 0;
+    ggml_status last_compute_status_ = GGML_STATUS_SUCCESS;
 
     sd::ComputeWorkspace::Measurement measure(ggml_cgraph* graph, size_t direct_bytes);
     std::vector<DeviceMemoryRequest> memory_requests(const std::vector<sd::BackendBufferSize>& sizes,
@@ -335,6 +336,8 @@ public:
                                              bool no_return                            = false,
                                              const std::function<bool()>& read_outputs = {});
 
+    ggml_status last_compute_status() const { return last_compute_status_; }
+
     void set_flash_attention_enabled(bool enabled) {
         flash_attn_enabled = enabled;
     }

src/model_manager.cpp

@@ -1613,7 +1613,8 @@ void ModelManager::remove_runtime_owner(uintptr_t owner_id) {
 
 ModelManager::CapacityCheck ModelManager::check_capacity(
     const DeviceMemoryRequest& request,
-    const std::vector<TensorState*>& states) const {
+    const std::vector<TensorState*>& states,
+    bool log_details) const {
     CapacityCheck result;
     if (request.compute_backend == nullptr || sd_backend_is_cpu(request.compute_backend)) {
         return result;
@@ -1631,16 +1632,23 @@ ModelManager::CapacityCheck ModelManager::check_capacity(
         }
         size_t free_bytes = 0, total_bytes = 0;
         ggml_backend_dev_memory(device, &free_bytes, &total_bytes);
+        const size_t weights_resident = compute_backend_resident_bytes(backend);
+        const size_t other_runtime    = other_runtime_resident_bytes(request.owner_id, backend);
+        const size_t resident         = add(weights_resident, add(other_runtime, request.runtime_resident_bytes));
+        if (log_details) {
+            LOG_WARN("model manager memory on %s: reported free %.2f MB / total %.2f MB, tracked weights %.2f MB / other runtime %.2f MB / current runtime %.2f MB",
+                        ggml_backend_name(backend),
+                        free_bytes / (1024.0 * 1024.0), total_bytes / (1024.0 * 1024.0),
+                        weights_resident / (1024.0 * 1024.0), other_runtime / (1024.0 * 1024.0),
+                        request.runtime_resident_bytes / (1024.0 * 1024.0));
+        }
         if (free_bytes == 0 && total_bytes == 0) {
             return SIZE_MAX;
         }
         // Vulkan's heap budget subtraction can underflow when usage exceeds the budget.
-        if (total_bytes > 0 && free_bytes > total_bytes) {
+        if (total_bytes > 0 && free_bytes > total_bytes && sd_backend_is(backend, "Vulkan")) {
             return size_t{0};
         }
-        const size_t resident = add(compute_backend_resident_bytes(backend),
-                                       add(other_runtime_resident_bytes(request.owner_id, backend),
-                                           request.runtime_resident_bytes));
         if (total_bytes > 0) {
             free_bytes = std::min(free_bytes, resident < total_bytes ? total_bytes - resident : 0);
         }
@@ -1786,7 +1794,7 @@ bool ModelManager::ensure_compute_backend_capacity(
         }
     }
 
-    const auto capacity                = check_capacity(request, required_states);
+    const auto capacity                = check_capacity(request, required_states, true);
     const std::string available_device = capacity.available_device_bytes == SIZE_MAX
                                              ? "unknown"
                                              : sd_format("%.2f MB", capacity.available_device_bytes / (1024.0 * 1024.0));

src/model_manager.h

@@ -157,7 +157,8 @@ private:
         }
     };
     CapacityCheck check_capacity(const DeviceMemoryRequest& request,
-                                 const std::vector<TensorState*>& states) const;
+                                 const std::vector<TensorState*>& states,
+                                 bool log_details = false) const;
 
     ggml_backend_buffer_type_t params_buffer_type_for(const TensorState& state) const;
     ggml_backend_buffer_type_t split_buffer_type_for(const TensorState& state) const;

src/pipeline/diffusion_engine.cpp

@@ -2766,7 +2766,8 @@ sd::Tensor<float> StableDiffusionGGML::decode_first_stage(const sd::Tensor<float
     auto decoded                      = first_stage_model->decode(n_threads, latents, vae_tiling_params, decode_video, circular_x, circular_y);
     const bool prefer_temporal_tiling = decode_video && first_stage_model->can_temporal_tile_decode();
     while (decoded.empty() &&
-           sd::backend_fit::prepare_vae_decode_retry_tiling(vae_tiling_params, prefer_temporal_tiling)) {
+           sd::backend_fit::prepare_vae_decode_retry_tiling(vae_tiling_params, prefer_temporal_tiling,
+                                                            first_stage_model->last_compute_status())) {
         decoded = first_stage_model->decode(n_threads, latents, vae_tiling_params, decode_video, circular_x, circular_y);
     }
     return decoded;

src/pipeline/video.cpp

@@ -470,11 +470,15 @@ namespace sd::pipeline {
         sd::Tensor<float> end_image;
 
         if (sd_vid_gen_params->init_image.data) {
-            start_image = sd_image_to_tensor(sd_vid_gen_params->init_image, request->width, request->height);
+            start_image = ensure_image_tensor_channels(
+                sd_image_to_tensor(sd_vid_gen_params->init_image, request->width, request->height),
+                sd->get_image_channels());
         }
 
         if (sd_vid_gen_params->end_image.data) {
-            end_image = sd_image_to_tensor(sd_vid_gen_params->end_image, request->width, request->height);
+            end_image = ensure_image_tensor_channels(
+                sd_image_to_tensor(sd_vid_gen_params->end_image, request->width, request->height),
+                sd->get_image_channels());
         }
 
         if (sd_version_is_minimax_h3(sd->version)) {
@@ -1416,7 +1420,9 @@ namespace sd::pipeline {
         sd::Tensor<float> video_mask = make_ltxav_video_denoise_mask(video_latent, 1.f);
 
         if (sd_vid_gen_params->init_image.data != nullptr) {
-            sd::Tensor<float> start_image = sd_image_to_tensor(sd_vid_gen_params->init_image, image_width, image_height);
+            sd::Tensor<float> start_image = ensure_image_tensor_channels(
+                sd_image_to_tensor(sd_vid_gen_params->init_image, image_width, image_height),
+                sd->get_image_channels());
             if (!apply_ltxav_condition_image_by_latent_index(sd,
                                                              start_image,
                                                              &video_latent,
@@ -1429,7 +1435,9 @@ namespace sd::pipeline {
         }
 
         if (sd_vid_gen_params->end_image.data != nullptr) {
-            sd::Tensor<float> end_image        = sd_image_to_tensor(sd_vid_gen_params->end_image, image_width, image_height);
+            sd::Tensor<float> end_image = ensure_image_tensor_channels(
+                sd_image_to_tensor(sd_vid_gen_params->end_image, image_width, image_height),
+                sd->get_image_channels());
             sd::Tensor<float> end_image_latent = encode_ltxav_condition_image(sd, end_image, "end");
             if (end_image_latent.empty()) {
                 return false;