Show HN: Jeva.cpp – a llama.cpp fork with JEV-compatible API for all LLMs

jeva.cpp is a fork of llama.cpp that adds a JEV-compatible decision API to llama-server, enabling Choice, Score and Noul evaluations directly from model logits while preserving standard autoregressive generation.

jeva.cpp is designed to work with all models and platforms supported by llama.cpp, reusing its existing model implementations and inference backends. The JEV decision API requires models that provide next-token vocabulary logits; other model types retain their original functionality.

LLM inference in C/C++

ggml / ops / maintainer PRs / dev stats / lib llama API / llama-server REST API

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:

llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF

llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF

| VLM session with llama cli | Built-in web UI against llama serve |

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 ZIHINT 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.

• 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 themaster branch

• Any help with managing issues, PRs and projects is very appreciated!

• Read the CONTRIBUTING.md for more information

• yhirose/cpp-httplib - Single-header HTTP server, used byllama-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