[
 {
  "id": "anemoi",
  "name": "Anemoi",
  "owner": "ecmwf",
  "licence": null,
  "latest_release": null,
  "release_date": null,
  "backends": null,
  "sources": [
   "https://www.ecmwf.int/en/about/media-centre/news/2025/ecmwfs-ensemble-ai-forecasts-become-operational"
  ],
  "notes": "Open-source framework used to train AIFS"
 },
 {
  "id": "comfyui",
  "name": "ComfyUI",
  "owner": null,
  "licence": null,
  "latest_release": null,
  "release_date": null,
  "backends": null,
  "sources": [
   "https://rits.shanghai.nyu.edu/ai/minimax-ships-h3-weights-with-the-us-and-eu-excluded/"
  ],
  "notes": "Claims MiniMax H3 runs in 12 GB with offload"
 },
 {
  "id": "core-ml",
  "name": "Core ML (via Core ML Tools)",
  "owner": "apple",
  "licence": "coremltools-bsd-style",
  "latest_release": "coremltools 9.0",
  "release_date": "2025-11-10",
  "backends": null,
  "sources": [
   "https://github.com/apple/coremltools",
   "https://pypi.org/project/coremltools/"
  ],
  "unverified": [],
  "notes": "Converts TensorFlow 1.x/2.x, PyTorch, scikit-learn, XGBoost and LibSVM to Core ML format for deployment through Xcode; Core ML runtime ships with Apple OSes (runtime licence not checked)"
 },
 {
  "id": "dgl",
  "name": "DGL",
  "owner": "dmlc",
  "licence": "apache-2-0",
  "latest_release": "2.2.1",
  "release_date": "2024-05-13",
  "backends": null,
  "sources": [
   "https://pypi.org/pypi/dgl/json",
   "https://github.com/dmlc/dgl"
  ],
  "notes": "No PyPI release since May 2024"
 },
 {
  "id": "executorch",
  "name": "ExecuTorch",
  "owner": "meta",
  "licence": "bsd-3-clause",
  "latest_release": "1.5.1",
  "release_date": "2026-09-22",
  "backends": "XNNPACK, Core ML (ANE), MPS (deprecated), Qualcomm, MediaTek, Samsung Exynos, Arm Ethos-U, Vulkan, OpenVINO, NXP, Cadence DSP, CUDA/Metal (experimental)",
  "sources": [
   "https://github.com/pytorch/executorch",
   "https://pypi.org/project/executorch/"
  ],
  "unverified": [],
  "notes": "AOT export (torch.export) to .pte, C++ runtime, 50 KB base footprint. Used in Instagram, WhatsApp, Quest 3, Ray-Ban Meta glasses"
 },
 {
  "id": "funasr",
  "name": "FunASR toolkit",
  "owner": "alibaba",
  "licence": "mit",
  "latest_release": null,
  "release_date": null,
  "backends": null,
  "sources": [
   "https://github.com/modelscope/FunASR",
   "https://github.com/modelscope/FunASR"
  ],
  "notes": "Model zoo includes Fun-ASR, SenseVoice, Paraformer, CAM++, Whisper"
 },
 {
  "id": "genesis",
  "name": "Genesis / Genesis World",
  "owner": "genesis-ai",
  "licence": "apache-2-0",
  "latest_release": "Genesis World 1.0",
  "release_date": "2026-05",
  "backends": null,
  "sources": [
   "https://github.com/Genesis-Embodied-AI/Genesis",
   "https://www.techcrunch.com/2025/07/01/genesis-ai-launches-with-105m-seed-funding-from-eclipse-khosla-to-build-ai-models-for-robots"
  ],
  "notes": "Multi-physics engine, Nyx renderer, Quadrants compiler (forked from Taichi, Jun 2025); about 30k GitHub stars"
 },
 {
  "id": "genie-sim-3-0",
  "name": "Genie Sim 3.0",
  "owner": "agibot",
  "licence": null,
  "latest_release": "3.0",
  "release_date": null,
  "backends": null,
  "sources": [
   "https://www.therobotreport.com/agibot-releases-go-2-foundation-model-embodied-ai/"
  ],
  "notes": "Simulation platform used for GO-2 sim-to-real"
 },
 {
  "id": "isaac-lab",
  "name": "Isaac Lab (on Isaac Sim)",
  "owner": "nvidia",
  "licence": "bsd-3-clause",
  "latest_release": "Isaac Lab 3.0 (referenced Mar 2026)",
  "release_date": "2025-11-06",
  "backends": "GPU-parallel physics",
  "sources": [
   "https://arxiv.org/abs/2511.04831",
   "https://www.originofbots.com/news/nvidia-gr00t-n17-hits-early-access-for-humanoids"
  ],
  "notes": "GPU-native successor to Isaac Gym; photoreal rendering, sensor sims, domain randomisation; Newton integration planned. Licence BSD-3 unverified"
 },
 {
  "id": "lerobot",
  "name": "LeRobot",
  "owner": null,
  "licence": null,
  "latest_release": null,
  "release_date": null,
  "backends": null,
  "sources": [
   "https://www.originofbots.com/news/nvidia-gr00t-n17-hits-early-access-for-humanoids"
  ],
  "notes": "GR00T N1.7 integration"
 },
 {
  "id": "litert",
  "name": "LiteRT (formerly TensorFlow Lite) and LiteRT-LM",
  "owner": "google",
  "licence": "apache-2-0",
  "latest_release": "ai-edge-litert 2.3.0",
  "release_date": "2026-10-06",
  "backends": "On-device; GPU and NPU details unverified",
  "sources": [
   "https://ai.google.dev/edge/litert",
   "https://github.com/google-ai-edge/LiteRT",
   "https://pypi.org/project/ai-edge-litert/"
  ],
  "unverified": [
   "backends"
  ],
  "notes": null
 },
 {
  "id": "llama-cpp",
  "name": "llama.cpp",
  "owner": "ggml-org",
  "licence": "mit",
  "latest_release": null,
  "release_date": null,
  "backends": "Metal, CUDA, Vulkan, SYCL, CANN (Ascend), HIP, Hexagon, OpenCL (Adreno), WebGPU, ZenDNN, MUSA, OpenVINO (in progress)",
  "sources": [
   "https://github.com/modelscope/FunASR",
   "https://github.com/ggml-org/llama.cpp"
  ],
  "notes": "1.5-bit to 8-bit integer quantization"
 },
 {
  "id": "mlc-llm",
  "name": "MLC LLM",
  "owner": "mlc-ai",
  "licence": "apache-2-0",
  "latest_release": null,
  "release_date": null,
  "backends": "Vulkan, ROCm, CUDA, Metal (macOS, iOS/iPadOS A-series), Intel GPU via Vulkan/Metal, WebGPU and WASM (browser), OpenCL on Adreno and Mali (Android)",
  "sources": [
   "https://github.com/mlc-ai/mlc-llm"
  ],
  "unverified": [
   "latest_release"
  ],
  "notes": "MLCEngine OpenAI-compatible REST, Python and JS API; builds on Apache TVM; companion WebLLM"
 },
 {
  "id": "monai",
  "name": "MONAI",
  "owner": null,
  "licence": "apache-2-0",
  "latest_release": null,
  "release_date": null,
  "backends": null,
  "sources": [
   "https://github.com/Project-MONAI/MONAI",
   "https://monai.io/"
  ],
  "notes": "Core, Label and Deploy components for medical imaging AI; NVIDIA and King's College London origin unverified"
 },
 {
  "id": "mujoco",
  "name": "MuJoCo (with MJX and MuJoCo Warp)",
  "owner": "google-deepmind",
  "licence": "apache-2-0",
  "latest_release": null,
  "release_date": null,
  "backends": null,
  "sources": [
   "https://github.com/google-deepmind/mujoco",
   "https://aiwiki.ai/wiki/gemini_robotics_2"
  ],
  "notes": "Monthly release cadence; MJX is a JAX branch; Gemini Robotics On-Device SDK ships a MuJoCo simulator"
 },
 {
  "id": "newton",
  "name": "Newton",
  "owner": "linux-foundation",
  "licence": "apache-2-0",
  "latest_release": null,
  "release_date": null,
  "backends": "GPU physics on NVIDIA Warp (requires Warp 1.18); MuJoCo Warp as primary backend",
  "sources": [
   "https://github.com/newton-physics/newton"
  ],
  "notes": "OpenUSD; differentiable. Initiated by Disney Research, Google DeepMind and NVIDIA; docs CC-BY-4.0"
 },
 {
  "id": "nvidia-cuopt",
  "name": "NVIDIA cuOpt",
  "owner": "nvidia",
  "licence": "apache-2-0",
  "latest_release": "26.10",
  "release_date": null,
  "backends": "GPU-accelerated",
  "sources": [
   "https://github.com/NVIDIA/cuopt"
  ],
  "notes": "Optimisation solver (not a neural model); Python API and server; TSP, VRP, PDP, LP, QP, MIP (beta)"
 },
 {
  "id": "nvidia-nim",
  "name": "NVIDIA NIM",
  "owner": "nvidia",
  "licence": null,
  "latest_release": null,
  "release_date": null,
  "backends": null,
  "sources": [
   "https://investor.nvidia.com/news/press-release-details/2026/NVIDIA-Launches-Cosmos-3-the-Open-Frontier-Foundation-Model-for-Physical-AI/default.aspx",
   "https://catalog.ngc.nvidia.com/orgs/nim/nvidia/models/alpamayo-1-5-10b/-"
  ],
  "notes": "Serves Cosmos 3 and Alpamayo 1.5"
 },
 {
  "id": "ollama",
  "name": "Ollama",
  "owner": "ollama",
  "licence": "mit",
  "latest_release": null,
  "release_date": null,
  "backends": "CPU/GPU details not fetched",
  "sources": [
   "https://ollama.com/library",
   "https://github.com/ollama/ollama/blob/main/LICENSE"
  ],
  "unverified": [],
  "notes": "Local LLM runner, GGUF-based"
 },
 {
  "id": "onnx-runtime",
  "name": "ONNX Runtime",
  "owner": "microsoft",
  "licence": "mit",
  "latest_release": "1.31.0",
  "release_date": "2026-10-09",
  "backends": "CPU: default CPU, Intel DNNL, Intel OpenVINO, XNNPACK. GPU: NVIDIA CUDA, NVIDIA TensorRT, DirectML, AMD MIGraphX, AMD ROCm (deprecated), WebGPU. IoT/edge/mobile: Intel OpenVINO, Rockchip NPU (preview), Arm Compute Library (preview), Android NNAPI, Arm NN (preview), CoreML (preview), Qualcomm QNN, XNNPACK. Other: Xilinx Vitis-AI, TVM, Huawei CANN, Azure (all preview)",
  "sources": [
   "https://github.com/microsoft/onnxruntime",
   "https://onnxruntime.ai/docs/execution-providers/",
   "https://pypi.org/project/onnxruntime/"
  ],
  "unverified": [],
  "notes": null
 },
 {
  "id": "openvino",
  "name": "OpenVINO",
  "owner": "intel",
  "licence": "apache-2-0",
  "latest_release": "2026.4.1",
  "release_date": "2026-10-01",
  "backends": "CPU (x86, ARM), Intel integrated and discrete GPU, Intel NPU",
  "sources": [
   "https://huggingface.co/aisingapore/Qwen-SEA-LION-v4.5-27B-IT",
   "https://github.com/openvinotoolkit/openvino",
   "https://pypi.org/project/openvino/"
  ],
  "notes": "Imports PyTorch, TensorFlow, ONNX, TensorFlow Lite, PaddlePaddle, JAX/Flax. Companion OpenVINO Model Server"
 },
 {
  "id": "pytorch-geometric",
  "name": "PyTorch Geometric (PyG)",
  "owner": "pyg-team",
  "licence": "mit",
  "latest_release": "2.8.0.post1",
  "release_date": "2026-07-20",
  "backends": "PyTorch 2.9 to 2.12",
  "sources": [
   "https://github.com/pyg-team/pytorch_geometric/releases",
   "https://pypi.org/pypi/torch-geometric/json",
   "https://github.com/pyg-team/pytorch_geometric"
  ],
  "notes": "2.8.0 adds RelBench-to-PyG converter, GRetriever example, LLM txt2qa; 2.7.0 added LPFormer, SGFormer, Polynormer"
 },
 {
  "id": "qualcomm-ai-runtime",
  "name": "Qualcomm AI Runtime (QAIRT) / GenieX",
  "owner": "qualcomm",
  "licence": null,
  "latest_release": null,
  "release_date": null,
  "backends": "Snapdragon devices",
  "sources": [
   "https://aihub.qualcomm.com/models"
  ],
  "unverified": [],
  "notes": "Runtime listed on Qualcomm AI Hub; GenieX (QAIRT, llama.cpp)"
 },
 {
  "id": "sglang",
  "name": "SGLang",
  "owner": null,
  "licence": null,
  "latest_release": null,
  "release_date": null,
  "backends": "Multi-GPU",
  "sources": [
   "https://rits.shanghai.nyu.edu/ai/minimax-ships-h3-weights-with-the-us-and-eu-excluded/"
  ],
  "notes": "Recommended multi-GPU (4 GPUs) serving for MiniMax H3"
 },
 {
  "id": "tensorrt",
  "name": "TensorRT",
  "owner": "nvidia",
  "licence": "proprietary",
  "latest_release": "11.4.0.106",
  "release_date": "2026-10-08",
  "backends": null,
  "sources": [
   "https://github.com/NVIDIA/TensorRT",
   "https://pypi.org/project/tensorrt/"
  ],
  "unverified": [],
  "notes": "Per-model support matrix (LLM, encoder NLP, vision, audio, diffusion, multimodal). Open-source components on GitHub are Apache 2.0; PyPI package declares Proprietary. Jetson not checked"
 },
 {
  "id": "tensorrt-llm",
  "name": "TensorRT-LLM",
  "owner": "nvidia",
  "licence": "apache-2-0",
  "latest_release": "1.2.1",
  "release_date": "2026-04-20",
  "backends": "Blackwell data-centre GPUs; Jetson and Thor edge support unverified",
  "sources": [
   "https://github.com/NVIDIA/TensorRT-LLM",
   "https://pypi.org/project/tensorrt-llm/"
  ],
  "unverified": [
   "backends"
  ],
  "notes": "GitHub README news to 17 Jul (PyPI may lag)"
 },
 {
  "id": "terratorch",
  "name": "TerraTorch",
  "owner": null,
  "licence": null,
  "latest_release": null,
  "release_date": null,
  "backends": null,
  "sources": [
   "https://huggingface.co/ibm-nasa-geospatial/Prithvi-EO-2.0-600M"
  ],
  "notes": "Tooling for Prithvi-EO-2.0 geospatial models"
 },
 {
  "id": "tflm",
  "name": "TensorFlow Lite for Microcontrollers (TFLM)",
  "owner": "google",
  "licence": "apache-2-0",
  "latest_release": null,
  "release_date": null,
  "backends": "DSPs, MCUs: Cortex-M, RISC-V, Hexagon, Xtensa; ports for Arduino, Espressif, Renesas, Silicon Labs, TI, Coral Dev Board Micro",
  "sources": [
   "https://github.com/tensorflow/tflite-micro"
  ],
  "unverified": [],
  "notes": "Rename to LiteRT for Microcontrollers not confirmed"
 },
 {
  "id": "tinyengine",
  "name": "TinyEngine (MCUNet)",
  "owner": "mit-han-lab",
  "licence": "mit",
  "latest_release": null,
  "release_date": null,
  "backends": "Microcontrollers (STM32F746 profiled)",
  "sources": [
   "https://github.com/mit-han-lab/mcunet"
  ],
  "unverified": [],
  "notes": "1.5 to 3x faster and 2.7 to 4.8x lower peak memory than TFLM, CMSIS-NN, MicroTVM"
 },
 {
  "id": "vllm",
  "name": "vLLM",
  "owner": null,
  "licence": null,
  "latest_release": null,
  "release_date": null,
  "backends": null,
  "sources": [
   "https://huggingface.co/tiiuae/Falcon-H1R-7B"
  ],
  "notes": null
 }
]