Aleksander Grygier
69b3cc406e
* ui : let the expanded sidebar be resized by dragging its edge Bring back the desktop sidebar resize handle that was dropped with the shadcn sidebar primitive. The width is clamped between 18rem and 32rem, persists across reloads, and resets on a double-click of the handle. The tab bar follows the same width so a wider sidebar never covers it. Assisted by: Claude (Opus 5.5 Medium) * ui : rubber-band the sidebar edge past its bounds and drag it shut Past the max width the edge resists harder the further it is pulled, and the same happens below the min width until the pull passes 9rem, where it snaps to the pointer and letting go hides the sidebar. A release outside the bounds springs the width back to the nearest one. Assisted by: Claude (Opus 5.5 Medium) * ui : show the sidebar edge strip faintly on hover and solid while dragging The strip is clipped to the sidebar's rounded corners through its own overlay, so the sidebar itself is never clipped. Assisted by: Claude (Opus 5.5 Medium) * ui : remember whether the desktop sidebar is open across reloads A phone opens the sidebar as an overlay, so it always starts closed there and its toggling never overwrites the desktop preference. Assisted by: Claude (Opus 5.5 Medium) * ui : fade the sidebar labels and conversation list with its width The fade follows the live width, so it tracks both the toggle's width transition and a drag below the minimum width. Assisted by: Claude (Opus 5.5 Medium) * ui : persist the sidebar width on release and clamp a restored one A drag now updates only the live width and writes it to localStorage once when released. A width restored from localStorage is clamped to the current bounds, so a value saved under older bounds does not stick. Assisted-by: Claude (Opus 5.5 Medium)
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:
# curl
curl -LsSf https://llama.app/install.sh | sh
# powershell
irm https://llama.app/install.ps1 | iex
- 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