Hugging Face

Unsloth

Open-source desktop app, web UI, and Python library for running and fine-tuning open-weight models locally. It serves models through an OpenAI-compatible API and trains them about twice as fast with roughly 70% less memory than standard pipelines.

Freemium

Data & ML Libraries

5/5

Unsloth builds directly on the Hugging Face Transformers and TRL ecosystem, loading base models from the Hub and exporting fine-tuned adapters back to it.

LlamaFactory

Open-source toolkit for fine-tuning more than 100 open-weight language and vision models with LoRA, QLoRA, full training, and preference methods such as DPO. Runs from YAML configs on the command line or from the LLaMA Board web UI without writing code.

Open Source

Data & ML Libraries

4/5

LlamaFactory is built on Hugging Face Transformers, PEFT, and TRL: it loads base models and datasets from the Hub by repository ID and exports merged weights in the standard Hub format.

Xiaomi MiMo

Xiaomi's open-weight, MIT-licensed LLM family, led by the omnimodal MiMo-V2.6-Pro (1.02T MoE, 42B active), which ranks among the strongest open-weight models for agentic and coding work at a low per-token price.

Freemium

LLM

4/5

MiMo's open weights, tokenizer, and model cards are published on Hugging Face for download and deployment.

MiniMax

MiniMax is a Chinese AI lab whose M3 open-weight model offers a 1M-token context, native multimodal input, and strong agentic coding, available as self-hosted weights, a low-cost API, and a Token Plan subscription.

Freemium

LLM

3/5

MiniMax publishes its open-weight model checkpoints on the Hugging Face Hub, where they can be downloaded, self-hosted, or served through Hugging Face's own inference options.

DeepSeek

Chinese open-weight LLM family under the MIT license, led by DeepSeek-V4.1-Flash, offering frontier-level results at very low API prices, with full self-hosting through vLLM, SGLang, and Ollama.

Freemium

LLM

3/5

DeepSeek publishes its open-weight model checkpoints on the Hugging Face Hub, where they can be downloaded, self-hosted, or served through Hugging Face's own inference options.

Ollama

The most widely used way to run open-weight LLMs locally — one command downloads and serves models like Llama, Qwen, DeepSeek, GLM, and MiniMax through an OpenAI-compatible API, with an optional paid Ollama Cloud tier for larger models than local hardware can handle.

Freemium

AI Infrastructure

3/5

Hugging Face hosts the model weights that Ollama pulls and runs locally; the two are commonly paired, discover a model on the Hub, then run it through Ollama.

Hugging Face Spaces

Hugging Face's hosting for ML demo apps: push a Streamlit, Gradio, or static app and it runs on a public URL, free on CPU.

Freemium

Hosting & Cloud

5/5

Hugging Face Spaces are Git repositories on the Hugging Face Hub that host Gradio, Streamlit, or Docker apps next to the models and datasets they load.

Gradio

Gradio is an open-source Python framework for rapidly building shareable demos and web interfaces for machine learning models, APIs, and Python functions with minimal code.

Open Source

Data Apps

3/5

Hugging Face Spaces is the standard free hosting target for a Gradio demo, deployed with a single `gradio deploy` command from the official Gradio CLI.

Langflow

An open-source, low-code visual builder for AI agents and RAG pipelines — drag-and-drop components on a canvas, model- and vendor-agnostic, with every flow exportable as an API or Python code. One of the most-starred AI projects on GitHub.

Open Source

Agentic AI

3/5

Langflow provides Hugging Face components for using hosted or local Hub models inside a flow.

llama.cpp

Open-source C/C++ engine that runs GGUF language and vision models on CPUs, Apple Silicon, and consumer GPUs. Its llama-server binary serves them through an OpenAI-compatible API with a built-in web UI.

Open Source

AI Infrastructure

5/5

llama.cpp downloads GGUF models straight from the Hugging Face Hub with its -hf flag, and Hugging Face model pages list llama.cpp among the local apps for running a model. The llama.cpp team is part of Hugging Face.

vLLM

Open-source, high-throughput inference and serving engine for large language models, exposing an OpenAI-compatible API. It is the most common way to self-host open-weight models in production on GPU and accelerator clusters.

Open Source

AI Infrastructure

4/5

vLLM loads models straight from the Hugging Face Hub by repository ID, and Hugging Face lists vLLM among the local apps and serving engines offered on its model pages.

LM Studio

Desktop app for downloading and running open-weight language models locally on macOS, Windows, and Linux, with a chat interface and a local OpenAI-compatible API server. It is free for personal and work use.

Freemium

AI Infrastructure

4/5

LM Studio's built-in model browser searches and downloads GGUF and MLX models directly from the Hugging Face Hub, and Hugging Face model pages offer LM Studio as a local app to open them in.

Groq

Fast LLM inference on Groq's own LPU hardware: unlike aggregators such as OpenRouter, Groq runs the compute itself, with low time-to-first-token and per-token pricing among the lowest of the major providers.

Usage Based

AI Infrastructure

4/5

Groq is a focused hosted API running models on its LPU hardware for speed; Hugging Face offers the largest model hub with serverless and dedicated inference endpoints. Groq for latency, Hugging Face for model breadth.

Together AI

Hosted inference cloud for open-weight models, serving 200+ chat, code, image, audio, and embedding models through an OpenAI-compatible API. Also rents dedicated GPU endpoints and clusters, and runs fine-tuning jobs.

Usage Based

AI Infrastructure

3/5

Together AI is a focused inference and training cloud with per-token APIs and GPU rental for open models; Hugging Face is the hub where those models are published, with its own inference endpoints on top. Pick Together AI for production serving, Hugging Face for discovery and the widest model selection.

Fireworks AI

Hosted inference platform for open-weight models, built by former members of Meta's PyTorch team and known for low latency on its custom serving engine. Offers per-token serverless APIs, dedicated GPU deployments, and fine-tuning.

Usage Based

AI Infrastructure

3/5

Fireworks AI is a hosted inference platform tuned for low latency, with fine-tuning and dedicated GPUs; Hugging Face is the hub where open models are published, with its own inference endpoints. Pick Fireworks AI for production speed, Hugging Face for discovery and model breadth.