b10f9ca58c spec : add DFlash2 support (local convolution + candidate selector) (#27342) (#27816)
* spec : add DFlash2 support (local convolution + candidate selector) (#27342)

* support DFlash2

* Add p_min in DFlash2

Assisted-by: Claude Opus 5

* Revert unnecessary changes

Assisted-by: Claude Opus 5

* Revert draft sampling in rejection sampling

Assisted-by: Claude Opus 5

* Refactor code structure

Assisted-by: Claude Opus 5

* Delete embedding scaling

Assisted-by: Claude Opus 5

* Gate output transforms on DFlash2

Assisted-by: Claude Opus 5

* Optimize Dflash 2 cost

Assisted-by: Claude Opus 5

* Avoid using atoi

Assisted-by: Claude Opus 5

* Modify comments

Assisted-by: Claude Opus 5

* Move llama_model_dflash_selector_top_k to llama-ext.h

Assisted-by: Claude Opus 5

* Formatting

Assisted-by: Claude Opus 5

* Apply patch to fix the mrope bug

Assisted-by: Claude Opus 5

* fix ci

Assisted-by: Claude Opus 5

* Fix graph number calculation

Assisted-by: Claude Opus 5

* rename hid and unary

Assisted-by: Claude Opus 5

---------

Co-authored-by: Jian Chen <jianchen0311@gmail.com>
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>

* revert top-k.cu changes

---------

Co-authored-by: Zihan Zhang <tiancaizhangdaxian@sjtu.edu.cn>
Co-authored-by: Jian Chen <jianchen0311@gmail.com>
2026-08-27 19:17:07 +02:00
2026-06-12 15:53:26 +02:00
2026-02-02 08:38:55 +02:00
2026-08-23 20:55:56 +03:00

llama.cpp

llama

Quick start

A few options to get llama.cpp installed on your machine:

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
VLM session with `llama cli` VLM session with llama cli Built-in web UI against `llama serve` running Qwen 3.6 Built-in web UI against llama serve

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 [In Progress] 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

Contributing

  • Contributors can open PRs
  • Collaborators will be invited based on contributions
  • Maintainers can push to branches in the llama.cpp repo and merge PRs into the master branch
  • 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
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