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Cognition's SWE-2 coding model matches Fable 5.1 at lower cost

Cognition has released SWE-2, a new coding model post-trained using reinforcement learning from Moonshot AI's Kimi K3 model. This new model reportedly matches Fable 5.1's performance on the FrontierCode benchmark but at a significantly lower cost. SWE-2 also introduces selectable reasoning-effort levels, trained in a single reinforcement learning run, and demonstrates improved efficiency and reduced detours on coding tasks compared to its predecessor, SWE-1.7. AI

IMPACT Sets a new cost-performance benchmark for coding models, potentially influencing future development and deployment strategies.

RANK_REASON New model release from a frontier lab (Cognition) with performance benchmarks. [lever_c_demoted from frontier_release: ic=1 ai=1.0]

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

Cognition's SWE-2 coding model matches Fable 5.1 at lower cost

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Signal score
52 / 100
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Newsworthiness bucket
Significant
New model release from a frontier lab (Cognition) with performance benchmarks. [lever_c_demoted from frontier_release: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release, product
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High
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Breaking (< 6h)
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COVERAGE [1]

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

    Cognition Releases SWE-2: A Kimi K3 Post-Trained Coding Model That Matches Fable 5.1 on FrontierCode at 64% Lower Cost

    <p>Cognition, the company behind the Devin coding agent, has released SWE-2, its most capable coding model to date. SWE-2 is post-trained with reinforcement learning from Kimi K3, Moonshot AI&#8217;s 2.8T-parameter open model. Cognition reports a score of 50.0% on FrontierCode 1.…