Open Source Models
Open-source AI,
no infrastructure.
Run Llama, Mistral, DeepSeek, Qwen, Gemma, and 136+ more open-weight models via a single API. No GPUs required. OpenAI-compatible.
Providers available
Featured model families
Llama 3
Meta
Meta's flagship open-weight models. Llama 3.3 70B matches GPT-4o on many benchmarks at a fraction of the cost.
DeepSeek
DeepSeek AI
Chinese open-source lab producing state-of-the-art coding and reasoning models. DeepSeek R1 rivals o1 at open-weight pricing.
Mistral
Mistral AI
European open-source AI models known for efficiency. Mistral 7B and Mixtral 8x7B set the standard for small, capable models.
Qwen
Alibaba Cloud
Qwen2.5 and QwQ are among the strongest open-weight models for coding and reasoning tasks, including 128k context variants.
Gemma
Google's open-weight Gemma models are compact and highly capable — Gemma 3 27B competes with models twice its size.
Phi
Microsoft
Microsoft's Phi models punch far above their weight class. Phi-4 14B performs comparably to much larger models on reasoning tasks.
All open-source models
136 open-weight models from 10 providers.
Showing 100 of 136 open-source models. View all →
Why use open-source models?
No vendor lock-in
Open weights mean the model can be hosted anywhere. Switch providers without changing your application.
Transparent pricing
No hidden model updates. Run the exact same checkpoint for months and get reproducible results.
Fine-tuning ready
Open weights let you fine-tune on your own data for domain-specific tasks — something closed models cannot offer.
Community audited
Thousands of researchers test open-source models. Known limitations are documented publicly.
Cost-effective at scale
Many open models are 10–100× cheaper per token than their closed equivalents with comparable quality.
No data training risk
Some providers don't train on your data when you use their hosted open-source inference.
Run any open-source model via API
No GPU setup. No Docker. Just an API key and one line of code.
Get started free