Cognition launches new SWE-2 model, Rivaling Fable 5.1 and GPT-Astra
Cognition has released SWE-2, an advanced AI coding model that claims to rival top-tier models like Fable 5.1 and GPT-Astra at a significantly lower cost. The model utilizes scaled reinforcement learning to improve reasoning and efficiency in software engineering tasks.
Why it matters
The rapid advancement of agentic coding models is fundamentally changing software development workflows and the economics of AI-assisted programming.
Today we’re introducing SWE-2, our most advanced coding model yet. It pushes the Pareto frontier of capability and cost, achieving 50.0% on FrontierCode 1.1 Main 1 , within one point of Fable 5.1 while being 64% cheaper.
With SWE-2, we scaled RL to the multi-trillion-parameter regime for the first time, building on the SWE-1.7 2 training infrastructure and recipe. The key addition is an RL algorithm that trains all reasoning-effort levels in a single run, advancing the whole cost–performance frontier.
The result is our closest model yet to the frontier. On FrontierCode 1.1 Main and DeepSWE 1.1, SWE-2 beats SWE-1.7 and Grok 4.6 on both score and cost, matches GPT-5.6 Sol and Fable 5/5.1 at a fraction of their price, and comes within a few points of GPT-6 Astra at a quarter of the cost.
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