LLM inference in C/C++
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LLM inference in C/C++
Distribute and run LLMs with a single file.
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
Open-source library of optimized deep learning operations (matmul, convolution, attention) for CPUs (x64, AArch64, RISC-V) and Intel GPUs. Used by PyTorch, TensorFlow, OpenVINO, and ONNX Runtime.
使用稠密算力卡对稀疏大显存主机进行加速,主机包括 AI Max+ 395、M3 512G、DGX Spark 等。
Embeddable, in-memory, document-oriented database with a high-level Query builder interface.
llama.cpp on a jailbroken PS5: run any GGUF model natively on the console, starting with Qwen 3.8
Official library for RaBitQ vector quantization and approximate nearest-neighbor search, in C++ and Python.
Run models larger than your RAM or VRAM by streaming MoE experts from SSD. Built on llama.cpp.
Fast fork of llama.cpp designed for Qwen3.8-Flash-Next
llama.cpp fork that abliterates at inference