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IOPaint is a free, open-source and fully self-hostable image inpainting and outpainting tool powered by AI models. It can erase unwanted objects, add or replace elements in images, generate text, and generate new pixels around images to enlarge them, with various models available for different tasks.
IUMB supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Jan is an open-source alternative to ChatGPT. It runs open-source AI models locally or connects to cloud models such as GPT and Claude. The download is offered for Mac. A memory feature is listed as coming soon.
Kokoro-82M is an open-weight text-to-speech model with 82 million parameters, released under the Apache 2.0 license. It delivers audio quality comparable to larger TTS models while being faster and more cost-efficient, and its weights can be deployed in both production and personal environments.
Limits provides machine-learning models, research, training resources, or evaluation tools.
llama.cpp guide is a blog post on SteelPh0enix's blog that explains how to run large language models (LLMs) locally on any hardware using llama.cpp. Published on 2024-10-28 and updated on 2024-12-25, the guide covers building llama.cpp, obtaining and quantizing models, running the server, configuring settings, and hardware requirements.
LLM provides machine-learning models, research, training resources, or evaluation tools.
LLM Papers provides machine-learning models, research, training resources, or evaluation tools.
LLM pricing calculator is a web page for estimating model costs per million tokens. It takes input, cached input and output token counts and reports cost per million input tokens, per million cached input tokens and per million output tokens. It notes that direct token-based price comparisons may not be entirely accurate because different models use different tokenizers.
LLM Resources Hub provides machine-learning models, research, training resources, or evaluation tools.
LLM Stats is an AI leaderboard that ranks GPT, Claude, Gemini, Llama, DeepSeek and more than 300 AI models by intelligence, speed and price. Scores are computed from public benchmarks and live API metrics.
LLMs Bullshit Benchmark provides machine-learning models, research, training resources, or evaluation tools.
Locally Uncensored provides machine-learning models, research, training resources, or evaluation tools.
Meituan Long Cat provides machine-learning models, research, training resources, or evaluation tools.
ML Resources supports machine learning models, deployment, inspection, datasets, or AI development workflows.
MMDeploy is documented at version 1.3.1 and covers getting started, converting, running, evaluating and quantizing models, building from source or Docker image, and SDK usage. Its backend support pages describe ncnn, ONNX Runtime, OpenVINO, PPLNN, SNPE, TensorRT, TorchScript, RKNN, TVM and Core ML, and its codebase support covers several OpenMMLab projects.
NuExtract 2.0 is a document information extraction model developed by NuMind. NuMind builds frontier multimodal large language models that convert documents into structured JSON and clean Markdown, available via SaaS or private enterprise deployment. The models are specialized for document extraction and deployed in industries including insurance, banking, and healthcare; for example, AXA increased its extraction accuracy from 30% to 97% after switching to NuExtract.
Ollama is a tool for running and building with open AI models locally or in the cloud on macOS, Windows and Linux. Its pricing page lists Free, Pro, Max, Team and Enterprise subscription plans, with paid plans including usage credits and cloud model access. The Free plan includes running models locally and starter usage credits.
Open WebUI is a self-hosted AI interface for running AI on the user's own hardware. It connects to local or cloud models including Ollama, OpenAI, Anthropic, or compatible services, and can be extended with Python. The project offers community-shared prompts, models, tools, and functions, and lists deployment options including on-premises or air-gapped setups. Installation can be done with a pip command.
OpenML supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Poolside AI provides machine-learning models, research, training resources, or evaluation tools.
Qwen is an AI project whose site lists models including Qwen3Guard, a safety guardrail model built on Qwen3 foundation models for detecting risk in prompts and responses. It also lists Qwen-Image-Edit, an image editing version of a 20B Qwen-Image model, and Qwen-MT, a translation model via Qwen API supporting 92 languages.
Sarvam provides machine-learning models, research, training resources, or evaluation tools.
The SEAL LLM Leaderboard is a resource from Scale Labs that provides expert-driven benchmarks and updated rankings for large language models. It evaluates capabilities including agentic coding, frontier reasoning, and safety alignment, with over 20 benchmarks and assessments of more than 100 models from leading AI labs and open-source contributors.
