Open-source SenseVoiceSmall model for Mandarin, Cantonese, English, Japanese, and Korean ASR, language ID, emotion recognition, and audio event detection.
A 14M-parameter LLM keeps a virtual fish tank alive on an $8 ESP32-S3 — distilled from a 26B teacher into 7.56 MB, no network.
37 tok/s from Qwen3-Next-80B (48 GB) on a 32 GB laptop, 24 without drafts vs 2.8 for llama.cpp; reading 62 vs 16 tok/s. Faster than llama.cpp on all 13 models compared in Q4_K_M. LLMs bigger than your RAM, pure C, CPU or GPU.
A minimalist, terminal-native coding agent written in C.
Fun-ASR speech recognition models, with native Hugging Face Transformers support for Fun-ASR-Nano and separate FunASR, vLLM and llama.cpp deployment paths.
React Native binding of llama.cpp
Local LLM, image&video&music generator, run codex with local models on your phone
CUDA on an Apple Silicon Mac over Thunderbolt with no NVIDIA driver: a C userspace NVIDIA driver (libtinynv) plus cudart/cublas shims running unmodified llama.cpp and stable-diffusion.cpp on an RTX 5090 eGPU