Cognition Releases SWE-2: A Kimi K3 Post-Trained Coding Model That Matches Fable 5.1 on FrontierCode at 64% Lower Cost
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’s 2.8T-parameter open model. Cognition reports a score of 50.0% on FrontierCode 1.1 Main, within 1 point of Fable 5.1 at 64% lower cost. It is also Cognition’s first model with selectable reasoning-effort levels, all trained in a single RL run. Is it deployable? Not on your own infrastructure.
Cognition has released SWE-2, a coding model created by adding reinforcement learning training on top of an existing large language model. The model scores within 1 point of a competitor model on a coding benchmark while operating at 64% lower cost, and it can be used at three different performance levels all trained in a single training run. SWE-2 is not available as open-source weights or a standalone API, and instead runs only within Cognition's Devin software product.
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