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Flint

Flint is a 40B parameter model developed by AI startup Recursive, designed for code understanding, debugging, feature implementation, and testing. It supports MacOS and has been integrated into Ollama for code intelligence agents.

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7related stories

7 related stories

Oct 22Thu
  1. The Decoder74

    Recursive releases its first model developed in collaboration with Eureka Machine

    AI startup Recursive has released its first language model, Flint. During the development process, the AI system named Eureka Machine participated in proposing ideas, building, testing, and planning subsequent experiments.

    Same story · 2 outlets

    Why it matters: Recursive publicly announces its first model developed with the assistance of an automated research system, allowing readers to observe how far AI-assisted R&D can go.

  4. TechCrunch · AI71

    Recursive has released a laptop-grade coding model called Flint, claiming it is mostly built with AI.

    Recursive releases its first model, Flint, a free coding model that can run on laptops, with almost the entire development process driven by AI. Recursive's automated research system, Eureka Machine, participated in almost every development step of Flint, enabling the team to complete the model construction in less than four months.

    Same story · 2 outlets
Oct 21Wed
  2. OpenHands Blog63

    Recursive Flint released on OpenHands: Open-source model helps local efficient coding workflows.

    Recursive Flint is released, a hybrid expert model with 4 billion parameters, designed for efficient local inference, activating only about 250 million parameters per token, achieving 125+ tokens/second on M4 Pro MacBook Pro, and reaching 150+ tokens/second on NVIDIA RTX Spark. OpenHands, as its first partner, supports the model's operation on local hardware, providing developers with an open-source coding model option.

    Same story · 2 outlets
  3. vLLM Blog60

    vLLM supported the Recursive Flint model on the first day.

    vLLM announced support on the day Flint was released, with both NVFP4 and BF16 checkpoints capable of running on a single GPU, decoding approximately 500 tokens/s per request on a single GB200 with a context of 100,000 tokens.

    Same story · 2 outlets

    Why it matters: The original text provided Flint's day-0 support on vLLM, single-card throughput data, and the step-by-step kernel optimization process, allowing readers to judge the engineering trade-offs of small-batch inference based on this.

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