The definitive vLLM runtime for dual RTX 2080 Ti 22GB + NVLink, delivering Qwen 27B local inference with maximum 200+ tok/s single-request decode with support of FP8 weight ( Join Discord :https://discord.gg/VFqVVySdMS )
A reading path for CPU performance engineering, from one instruction to production inference. Primary sources only, with a runnable benchmark for every section.
RTX 6000 Pro Wiki — Running Large LLMs (Qwen3.5-397B, Kimi-K2.5, GLM-5) on PCIe GPUs without NVLink
Trustworthy AI related projects
BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.
Recipes to scale inference-time compute of open models
Your iPhone helps your Mac run a 27B model: faster prompt reading and more context over a USB-C cable
Dataflow compiler for QNN inference on FPGAs
Open decision models from 0.8B to 27B: a calibrated probability for every option in one pass, and a short thought only when unsure. Engine for vLLM, llama.cpp and MLX.
“AI-Compass”将为社区指引在 AI 技术海洋中航行的方向,无论你是初学者还是进阶开发者,都能在这里找到通往 AI 各大方向的路径。旨在帮助开发者系统性地了解 AI 的核心概念、主流技术、前沿趋势,并通过实践掌握从理论到落地的全过程。
Official inference library for pre-processing of Mistral models
A unified library for building, evaluating, and storing speculative decoding algorithms for LLM inference in vLLM
An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
Inference code for scalable emulation of protein equilibrium ensembles with generative deep learning
sbi is a Python package for simulation-based inference, designed to meet the needs of both researchers and practitioners. Whether you need fine-grained control or an easy-to-use interface, sbi has you covered.
This repository contains tutorials and examples for Triton Inference Server
Python Computer Vision & Video Analytics Framework With Batteries Included
AIPerf is a comprehensive benchmarking tool that measures the performance of generative AI models served by your preferred inference solution.
DoubleML - Double Machine Learning in Python
A Python library for simulation-based inference with deep learning
Vui Nano — a small, context-aware text-to-speech model trained on real conversations. 219M active params (305M total), Apache 2.0, voice cloning, streaming, runs on CPU (dependency-free C build). Ships with a full real-time voice assistant: WebRTC, ASR, local LLM, OpenAI Realtime API compatible.
A Python implementation of active inference for Markov Decision Processes
Up to 4× faster LLM decoding on Apple Silicon, lossless. Native MLX port of DeepSeek's DSpark & z-lab's DFlash speculative decoding — Gemma-4, Qwen3.8, Muse-Glimmer, Nemotron, LFM2.5, Ornith-1.0, ternary Bonsai-27B.
On-device Speech-to-Intent engine powered by deep learning
Frontier-class open models on a free Kaggle TPU v5e-8: GLM-5.3-Flash 320B MoE (~165 tok/s, our own JAX engine) and Qwen3.8-27B bf16 (~130 tok/s), 262k context, prefix caching. Works with Claude Code, Codex, opencode and pi.
Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
Gaussian processes in JAX and Equinox.
PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
Official PyTorch inference for Breeze TTS 2
[NeurIPS D&B '25] The one-stop repository for LLM unlearning
Monty is a sensorimotor learning framework based on the thousand brains theory of the neocortex.
High-performance, light-weight C++ LLM and VLM Inference Software for Physical AI
A common base representation of python source code for pylint and other projects
Don't memorize ML. Understand it from first principles including Inference, Cuda, Deep Learning, Data Science and Reinforcement Learning
An inference chip design that runs a real LLM (Qwen2.5-0.5B) on FPGA — one transformer decoder layer in RTL, every silicon value bit-exact against a golden model. 0.56 tok/s measured, a 140× climb, full evidence trail.
Causal Inference in Python
Self-hosted AI agent OS. Your memory, chat, agents, and files stay on hardware you own, offline by default, cloud by choice. Offline AI memory (taOSmd), self-hosted multi-framework group chat, a full web desktop + app store, and auto-clustering across the consumer hardware you already have (Orange/Raspberry Pi, Mac mini, gaming PC).
A Tree Search Library with Flexible API for LLM Inference-Time Scaling
Our inference and training framework to run on the Cosmos Models
A research-oriented framework for building optimization-driven decision intelligence systems, integrating causal inference, risk modeling, and AI pipelines for large-scale socio-technical systems
EdgeRock: Strong Reasoning at Constant Memory. Multimodal models with O(N) generation and O(1) persistent history. Inference and evaluation code.
From teacher to tiles — a from-scratch LLM distillation & serving engine: custom Triton/CUDA kernels, FSDP distillation, paged-KV continuous batching, speculative decoding, a Rust gateway, a JAX oracle, and interpretability tooling.
SLA: Beyond Sparsity in Diffusion Transformers via Fine-Tunable Sparse–Linear Attention
Laplace approximations for Deep Learning.
sparkrun - launch, manage, and stop LLM inference workloads on NVIDIA DGX Spark systems. Live support: https://discord.com/invite/GH5kRgv6ZD
Inference engine for Intel devices. Serve LLMs, VLMs, Whisper, Kokoro-TTS, Embedding and Rerank models over OpenAI endpoints.
Triton Model Analyzer is a CLI tool to help with better understanding of the compute and memory requirements of the Triton Inference Server models.
SparkDiffusion: Accelerating DiT video generation by 265× via joint Sparsity, Distillation, Quantization, etc.
high-performance inference and serving library for interactive autoregressive video and world models
Sequential Monte Carlo in python
Design, conduct and analyze results of AI-powered surveys and experiments. Simulate social science and market research with large numbers of AI agents and LLMs.
Remory: Learning Residual Memory for Context Compaction
Small client for media model inference
An educational Jev-like visual inference experiment on Apple Silicon: shared context, direct candidate scoring, and local visual demos.
Evolving Multimodal Inference Programs: LLM-guided evolutionary search for accurate and efficient vision-language inference.
lithos-metal: high-performance LLM inference kernels and serving for Apple silicon.
A unified, torch-native training framework for MTP and block-parallel speculative decoding.
AI Agent Identity and Access Management and Inference Firewall
One command turns a DGX Spark or ASUS Ascent GX10 into a private AI server: seven measured, pinned AI lanes (text up to 1M tokens, images, video with sound), run from a local cockpit on a laptop or a phone. Nothing leaves the box.
斑海豹 — Phocinae-Largha-150M-v1: a 144.3M bilingual decision model. Tiny model. Big decisions. 小海豹,大决断。