Recursive releases its first model, Flint: a 40B-total, 2.5B-active open-weights local coding model under Apache 2.0, running at 125+ tok/s on a MacBook
On Oct 21, Recursive, the startup founded by Richard Socher, released its first model, Flint: a 39.8B-total MoE coding model with about 2.5B active parameters per token, with weights on Hugging Face under Apache 2.0. Recursive says it leads sub-50B MoE models on SWE-Bench Pro v2, Terminal-Bench 2.1 and SWE-Bench Verified, runs at 125+ tok/s on an M4 Pro MacBook Pro, and was built from scratch in under four months with its automated research system, the Eureka Machine, contributing to nearly every part of the stack.
Key Takeaways
- Scale: 39.8B total, ~2.5B active incl. output head; 256 routed experts pick 6 plus 1 shared expert; Apache 2.0 (model card)
- Benchmarks (vendor-reported): Terminal-Bench 2.1 54.9%, SWE-bench Verified 74.2%; the card lists SWE-bench Pro v2 at 89.7%
- Speed (vendor-reported): 125+ tok/s on M4 Pro MacBook Pro, 150+ tok/s on 64GB RTX Spark at short contexts, up to 2x comparable models
- Context: 262,144 tokens in the model card config; the blog says up to 512K, best within 256K
- Ecosystem: day-one llama.cpp, Ollama, LM Studio, vLLM, SGLang, plus the open-source rec local engine; free to try on OpenCode and Pi
Linked Models & Agents:
