Recursive Unveils Flint, a Laptop-Ready Coding Model Largely Built by AI
Recursive, an AI startup founded last year, is starting to live up to its name. The company, which aims to build AI that can improve itself, released its first model, Flint, on Wednesday. Flint is a free coding model that runs on a laptop and was built largely with the help of AI.
Built by AI, in Under Four Months
Recursive's automated research system, which it calls the Eureka Machine, assisted with nearly every step of Flint's development, according to the company. That enabled a small team to build the model from scratch in under four months.
The Eureka Machine generates ideas, runs experiments, and uses the results to decide what to try next. According to the company's launch video, it contributed to nearly every part of building Flint, from pre-training to post-training and inference.
An Early Test of Recursive Self-Improvement
Flint is an early public test of recursive self-improvement—the idea that AI can build better AI, which in turn builds even better AI. It is also one of the most debated ideas in the industry. Some researchers fear that self-improving AI could slip out of human control. For now, Recursive's version is more limited: an AI research assistant overseen by people that produced a model small enough for a laptop.
Funding and Leadership
The company emerged from stealth in May 2026 with $650 million in funding at a $4.65 billion valuation, from backers including GV, Nvidia, and AMD Ventures. Recursive is led by CEO Richard Socher, Salesforce's former chief scientist.
Private, Offline, and Free
Because Flint runs on a user's own computer rather than a company's cloud servers, developers can use it offline, keep their code private, and avoid the usage fees that AI cloud services charge based on how much text the model processes. The model is free to download on Hugging Face under the Apache 2.0 license, an open-source license that allows free use and modification.
Efficient by Design
Flint is a mixture-of-experts model, meaning it uses only a small slice of itself for any given task: just 2.5 billion of its 40 billion settings, known as parameters, at a time. That makes it light enough for an ordinary laptop and far smaller than Meta's Muse Spark Open, an open model built for Macs that was released last week. Muse Spark Open uses 816 billion parameters and requires at least a terabyte of memory.
Flint is also fast. In Recursive's tests, it generated about 131 tokens (chunks of text) per second on a MacBook Pro with Apple's M4 Pro chip—roughly twice the 58 to 69 tokens per second that similar models managed on the same machine, including Google's Gemma 4 and Nvidia's Nemotron 3.5 Lightning. On Nvidia's RTX Spark, Flint topped 150 tokens per second.
Benchmark Performance
On SWE-Bench Verified, a benchmark that measures how well AI can fix real-world software bugs, Flint outperformed other models under 50 billion parameters. On Recursive's own average across six tests, only one model, Alibaba's Qwen3.8 27B, scored higher than Flint.
Early Reviews and Limitations
The company acknowledged that Flint would need more guidance than the 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, including a to-do list app and a tool that scours the web for research. He found that smaller coding models often ran into errors or were slow compared to Claude or Codex, but Flint nailed his coding requests every time.
via TechCrunch AI