@ryanallis9
Ryan AllisARR verified on AI LoungeFounder▲268
CEO, AI Lounge & SaasRise
Oct 22 · Link · Agents, AI Engineering · Austin

Recursive releases Flint, a 40B open-weight coding model that runs on laptops

Is this going to kill Anthropic's revenue from Claude code? Will we all just run local coding models on our own hardware in a year or two.

Recursive logoRecursive releases Flint, a 40B open-weight coding model that runs on laptopsFlint has 40 billion total parameters with 2.5 billion active per token, and Recursive reports 54.9% on Terminal-Bench 2.1, 89.7% on SWE-bench Pro v2 and 74.2% on SWE-bench Verified. Those are the company's own measurements, and it says the model generates more than 125 tokens per second on an M4 Pro MacBook Pro. The weights are on Hugging Face with a recommended context of 256k tokens. Recursive says a small team built the model in under four months, using its Eureka Machine to propose and test training recipes, quantization and kernels. The NVFP4 quantized version scores within 0.7 points of the 16-bit model on the company's benchmarks. Recursive is led by Richard Socher, the former Salesforce chief scientist. For builders, the release offers a coding model under a permissive license that runs on a laptop without API fees. Because the scores come from the vendor, teams should run their own evaluations on their repositories before swapping it into an agent stack.AI Lounge News · via Recursive · Read the story →
agentic engineering

Comments2

  • @milesgurule-png
    Miles Gurule
    15 · Founder of Forge Labs · I built an AI sales team that finds local businesses, designs their new site, and plans my walk-in route
    Oct 23

    I run Ollama locally and it's great for small stuff, but for real multi-file work I still reach for Claude Code. I think local models eat the cheap, simple tasks first and the hard agentic work stays in the cloud for a while. Curious if Flint's SWE-bench numbers hold up on messy real repos.

  • @rkeshwani
    Rohit Keshwani
    AI tinkerer - Self proclaimed Prophet of AI
    4d ago

    I haven't benchmarked this one but it looks like it was distilled on Gemini. The cost of hardware has now inflated where subscriptions actually make sense. Unless an intelligent individual or company increases the intelligence density of these models to run on lower end or lower capacity (VRAM) hardware. Infact the new laptops for 128gb which is what you need to run frontier class models are going to be $3k+. So you'll run basic computer use, writing documents and emails locally. To do actual useful engineering or design work you will use frontier. Not to mention ease of use. Right now the steps to get a local model running are greater than buying a frontier ai subscription you can use in your browser. Businesses at the small and mid level are still using AI for writing documents instead of ACTUAL work but most people are too dumb to install local AI. This is the sweet spot for frontier labs (low usage with enterprise level subscriptions)

Log in to join the thread.