mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2026-09-21 21:47:27 -05:00
Max Krasnyansky
0c3626ec06
* hex-dma64: enable support extended buffer mappings and 64bit dma hex-dma64: expand binary ops to support more DMA scenarios hex-dma64: add binary-ops.h hex-dma64: add --hex-dma64 to run.py and fix minor issues hex-dma64: update SSM_CONV to use dma with proper support for 64bit hex-ops: remove obsolete gate for % 128 in binary ops hex-l2: dont check weight tensors against dirty ranges hex-dma64: most binary ops now support dma hex-dma: use dma_addr_t instead of plain uint64_t to avoid overhead on older targets hex-dma: update all dma users to use dma_data (instead of pointers) hex-dma64: simplify lazy buffer mapping and clonning hex-fusion: factor out try_fuse_common that checks for dma64 buffers hex-bufs: minor cleanup for mmaping logic hex-bufs: simplify buffer clonning hex-ssm-conv: tighten gating checks and check vtcm size in kparams hex-binary: fix incorred mod/wrap in scalar ops hex-binary: make sure to call precompute kparams in support checks hex-dma64: update addr handling in mm,concat,binary hex-dma64: fixing up leftover of dma_addr_t conversion hex-binary: redo the kernel selection again and fix regressions in MOEs hex-binary: specialize per-type/per-op hex-binary: vtcm-layout and per-src dma-queue hex-dma64: update dma_push to transparently handle 64bit/extended * hex-cpy: fix improper rebase with the fixes for cont. tensors * hex-dma-cpy: update CPY to use safe dma rows/size limits * hex-mmap: bump number of mmaps to 64 to allow avoid eviction in larger models * hex-dma: add support for the secondary ring as a fallback for too-large transactions * hex-rope: fix freq_factors access with 64bit dma * hex-dma: audit all ops for proper use/gards for 64bit addresses * hex-dma64: uninline glu-compute funcs to avoid register pressure due to 64bit addr math * hex-dma64: refactor binary ops to separate dma loops * hex-devel: add inspect script to help with dbg and analysis * hex-dma: refactor dma-pipelines in unary-ops * hex-dma: rewrite softmax to use dma * hex-dma: rewrite GDN dma loops and improve HVX register usage * hex-gdn: fuse GDN+CPY * hex-mm: factor out HVX solver * hex-mm: remove hvx-flat kernels, the chunked version now handles vtcm limits much better * hex-buffs: reject huge buffer allocations that we cannot memory map * hex-inspect: add logic to look for float promo calls * hex-mm: reduce HVX register spills in HVX prompt kernels * hex-bufs: do not double count buffers from tensors in the same op * hex-roll: fix merge conflict * hex-dma: reroute all matmul ddr kernels to new chunked dma/vtcm kernels * hex-dev: update developer docs to include inspection for register spils and float promos * hex-ops: forgot to add new headers * hex-softmax: fix gpt-oss dims * hex-dma64: cleanup dma_addr_t casts * hex-dma64: add support for dma/vtcm for flash-atten with sinks * hex-mm-add: fix MUL_MAT+ADD fusion with bias.weights in extended bufs * hex-add-id: add support for dma for src1 (exp. table) * hex-dma: imrpove v73 fallback paths * hex-bufs: do not drop extended mappings during va defrag * hex-scripts: fix flake8 warnings * hex-docs: fix editor-config warnings * hex-inspect: fix warnings from ty
llama.cpp
LLM inference in C/C++
ggml / ops / maintainer PRs / dev stats / lib llama API / llama-server REST API
Quick start
A few options to get llama.cpp installed on your machine:
- Visit https://llama.app and follow the instructions
- Run with Docker - see our Docker documentation
- Download pre-built binaries from the releases page
- Build from source by cloning this repository - check out our build guide
Once installed:
# Download and run a model directly from Hugging Face
llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF
# Launch OpenAI-compatible API server
llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF
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Description
The main goal of llama.cpp is to enable LLM (and VLM) inference with minimal setup and state-of-the-art performance on
a wide range of hardware - locally and in the cloud.
- Plain C/C++ implementation without any dependencies
- Apple silicon is a first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks
- AVX, AVX2, AVX512 and AMX support for x86 architectures
- RVV, ZVFH, ZFH, ZICBOP and ZIHINTPAUSE support for RISC-V architectures
- 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use
- Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP and Moore Threads GPUs via MUSA)
- Vulkan and SYCL backend support
- CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacity
The llama.cpp project is build on top of the ggml library.
Supported backends
| Backend | Target devices |
|---|---|
| BLAS | All |
| BLIS | All |
| CANN | Ascend NPU |
| CUDA | Nvidia GPU |
| HIP | AMD GPU |
| Hexagon | Snapdragon |
| IBM zDNN | IBM Z & LinuxONE |
| MUSA | Moore Threads GPU |
| Metal | Apple Silicon |
| OpenCL | Adreno GPU |
| OpenVINO [In Progress] | Intel CPUs, GPUs, and NPUs |
| RPC | All |
| SYCL | Intel GPU |
| VirtGPU | VirtGPU APIR |
| Vulkan | GPU |
| WebGPU | All |
| ZenDNN | AMD CPU |
Documentation
Tools
Development
- How to build
- Running on Docker
- Build on Android
- Multi-GPU usage
- Performance troubleshooting
- GGML tips & tricks
- XCFramework
- Completions
- Models
- Release process
Contributing
- Contributors can open PRs
- Collaborators will be invited based on contributions
- Maintainers can push to branches in the
llama.cpprepo and merge PRs into themasterbranch - Any help with managing issues, PRs and projects is very appreciated!
- Read the CONTRIBUTING.md for more information
Acknowledgements
- yhirose/cpp-httplib - Single-header HTTP server, used by
llama-server- MIT license - nothings/stb - Single-header image format decoder, used by multimodal subsystem - Public domain
- nlohmann/json - Single-header JSON library, used by various tools/examples - MIT License
- mackron/miniaudio - Single-header audio format decoder, used by multimodal subsystem - Public domain
- sheredom/subprocess.h - Single-header process launching solution for C and C++ - Public domain