Recursive, an AI startup founded last year, released its first model on Wednesday: Flint, a free coding model that runs on a laptop and was built largely with the help of AI.
The company says its automated research system, the Eureka Machine, contributed to nearly every step of Flint's development, letting a small team build the model from scratch in under four months. Eureka's contributions reportedly include a sparser model shape, low-bit training that shrank Flint by 71% with almost no quality loss, and custom kernels that speed up computations.
Flint is an early public test of recursive self-improvement, the debated idea that AI can build better AI. Some researchers worry self-improving AI could slip out of human control; Recursive's version is more limited, an AI research assistant overseen by people that produced a model small enough for a laptop.
Because Flint runs on a user's own computer rather than cloud servers, developers can work offline, keep code private and avoid usage fees. It is free to download on Hugging Face under the Apache 2.0 license.
Flint is a mixture-of-experts model, using just 2.5 billion of its 40 billion parameters at a time. In Recursive's tests it generated about 131 tokens per second on a MacBook Pro with an M4 Pro chip, roughly twice the 58 to 69 tokens per second managed by similar models on the same machine, including Google's Gemma 4 and Nvidia's Nemotron 3.5 Lightning. On Nvidia's RTX Spark it topped 150 tokens per second.
On SWE-Bench Verified, a benchmark for fixing real-world software bugs, Flint outperformed other models under 50 billion parameters. On Recursive's own average across six tests, only Alibaba's Qwen3.8 27B scored higher.
The company acknowledged Flint needs more guidance than big paid coding assistants and suggested breaking large tasks into smaller steps. Still, early reviews were positive: Wired's Will Knight used Flint on a Mac with 48GB of memory to build several small programs and found it nailed his coding requests every time.
Recursive emerged from stealth in May with $650 million in funding at a $4.65 billion valuation, from backers including GV, Nvidia and AMD Ventures. It is led by CEO Richard Socher, Salesforce's former chief scientist. The company previously told TechCrunch that its $410 million compute deal with Amazon Web Services in June was "less about headcount and more about agent count."
The longer-term goal, Socher told Wired, is for the Eureka Machine to achieve full recursive self-improvement, with humans overseeing the process and able to stop it if something goes wrong.
Source: TechCrunch