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Recursive Superintelligence releases Flint, a 40B MoE coding model

By PulseAugur Editorial · [1 sources] ·

Recursive Superintelligence has launched Flint, a 40B parameter Mixture-of-Experts (MoE) model designed for coding agents. This model, which uses 2.5B active parameters per token, was developed with the assistance of Recursive's automated research system, Eureka Machine. Flint demonstrates strong performance on coding benchmarks like IFEval and SWE-bench, and is optimized to run efficiently on Apple Silicon Macs and NVIDIA GPUs with 48GB of memory. AI

IMPACT Optimized for local execution on consumer hardware, this model could accelerate agent development and deployment for developers with limited resources.

RANK_REASON Frontier-lab model release with system card [lever_c_demoted from frontier_release: ic=1 ai=1.0]

Read on MarkTechPost →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Recursive Superintelligence releases Flint, a 40B MoE coding model

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Frontier-lab model release with system card [lever_c_demoted from frontier_release: ic=1 ai=1.0]
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COVERAGE [1]

  1. MarkTechPost TIER_1 English(EN) · Asif Razzaq ·

    Recursive Releases Flint, an Open-Weight 40B MoE Local Coding Model for Agents with 2.5B Active Params

    <p>Recursive has released Flint, an Apache 2.0 local coding model with 40B total and 2.5B active parameters. It reports 74.2% on SWE-bench Verified and 125+ tokens per second on an M4 Pro MacBook Pro.</p> <p>The post <a href="https://www.marktechpost.com/2026/10/21/recursive-flin…

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