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What changed in AI, one story at a time. Each one links to its primary source, and facts stay apart from interpretation.

Last updated ·

Wednesday, October 21UTC

  1. New
    RecursiveFlintModels

    Recursive releases Flint, a local coding model built with automated research

    Recursive released Flint, a 40-billion-parameter mixture-of-experts coding model with roughly 2.5 billion active parameters per token. The maker says its Eureka Machine helped develop the model and reports strong coding benchmarks and local inference speed; those are vendor measurements. The official model card specifies limitations, hardware and runtime differences, so teams should test their own workflows.

    Recursive3 sources

  2. New
    RecursiveFlint weightsPricing & Access

    Recursive makes Flint weights available under Apache 2.0

    Recursive published Flint model weights on its official Hugging Face repository under Apache 2.0. The release supports local deployment, subject to hardware and serving setup; the BF16 checkpoint is about 80 GB and the model card documents a 262,144-token configuration. Hosted API terms remain separate from the weight license.

    Recursive2 sources

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