MIT Licensed Local AI Models
These models carry the MIT license, one of the most permissive options available, which means free commercial use with virtually no strings attached.
Phi-4 14B
Microsoft · MIT
Microsoft's research-driven Phi-4 focuses on synthetic high-quality training data, producing a 14B model that outperforms much larger models on coding and mathematical reasoning benchmarks. MIT licensed with zero usage restrictions for commercial projects.
Min VRAM
8 GB
Context
16K
Run with Ollama
ollama run phi4:14bDeepSeek R1 Distill 8B
DeepSeek · MIT
A distilled version of DeepSeek's R1 reasoning model that inherits chain-of-thought problem-solving capabilities in a compact 8B package. One of the few small models that can reliably work through multi-step math and logic problems without external tooling.
Min VRAM
5 GB
Context
128K
Run with Ollama
ollama run deepseek-r1:8bDeepSeek V4 Flash
DeepSeek · MIT
The faster, more practical sibling of the 1.6-trillion-parameter DeepSeek V4 Pro. At 284B total it activates only ~13B parameters per token, so once loaded it generates far faster than its size suggests — but even at 4-bit it needs roughly 180 GB of memory, putting it in 256 GB+ unified-memory Mac or multi-GPU server territory. MIT licensed, with a 1M-token context window.
Min VRAM
~180 GB (Q4)
Context
1M
Run with Ollama
ollama run deepseek-v4-flashOrnith 1.0 35B
DeepReinforce · MIT
Scores 75.6% on SWE-bench Verified — one of the highest results for any open-weight coding model and above most paid assistants. From the lab DeepReinforce, trained with RL self-improvement for terminal control and tool calling. MIT licensed, 262K context. There is no Ollama library tag yet — pull the GGUF directly with ollama run hf.co/deepreinforce-ai/Ornith-1.0-35B-GGUF.
Min VRAM
20 GB
Context
262K
Run with Ollama
ollama run hf.co/deepreinforce-ai/Ornith-1.0-35B-GGUFWant to mix in more filters?
Open the faceted model browser to combine VRAM, family, license, developer and task filters, then sort the results your way.