Model Card: Recursive Flint
Recursive Flint: a 40B-parameter MoE model (256 routed experts plus 1 shared expert, 6 routed experts active per token, ~2.5B active parameters), 262,144-token native context (official guidance caps practical use at 256K), Apache 2.0 license, released 2026-10-21 and covered by both TechCrunch and Wired. It scores 74.2% on SWE-bench Verified (edging out Qwen3.6-35B-A3B's own-reported 73.4%), 89.7% on SWE-bench Pro v2, 54.9% on Terminal-Bench 2.1, and 80.3% on LiveCodeBench v6 — the best self-reported scores among MoE models under 50B parameters. On a MacBook Pro M4 Pro it hits 131 tokens/s, nearly double the 58–69 tokens/s of comparable models like Gemma 4 and NVIDIA's Nemotron 3.5 Lightning, and tops 150 tokens/s on an RTX Spark. Quantizing to NVFP4 costs only 0.7 points versus the 16-bit checkpoint. There's no official paid API — Flint is a download-and-run open-weight model, though OpenRouter currently lists a free promotional hosted version. Recursive is led by Richard Socher, Salesforce's former chief scientist, and emerged from stealth in May 2026 with $650M raised at a $4.65B valuation. Flint is the company's first public model, and its headline claim is that almost the entire build pipeline — architecture search, quantization recipe, inference kernels — was handled by Recursive's own automated R&D system, the Eureka Machine, with a small team shipping it in under four months.