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SWE-2 is Cognition’s coding model.
Coding / product dossier
A coding model in Devin Desktop and CLI optimized for lower cost and fewer turns.
Product brief
SWE-2 is Cognition's new coding model, post-trained from Kimi K3 with RL that optimizes for cost and capability at the same time. It hits 50.0% on FrontierCode 1.1 Main, within a point of Fable 5.1 at 64% less, and lands within a few points of GPT-6 Astra at a quarter of the cost. Compared to SWE-1.7 it takes 58% fewer turns and costs 81% less while scoring higher. Available now in Devin Desktop and CLI.
Why we selected it
A technically specific coding-model release that targets both capability and operating cost, available in desktop and CLI workflows.
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Only capabilities supported by the product information we collected are listed here.
SWE-2 is Cognition’s coding model.
The model is post-trained from Kimi K3 with reinforcement learning intended to optimize cost and capability together.
SWE-2 is available in Devin Desktop and CLI.
The description reports that SWE-2 takes 58% fewer turns than SWE-1.7 while scoring higher.
Best-fit use cases
FAQ
SWE-2 is Cognition’s coding model, post-trained from Kimi K3 with reinforcement learning.
It is available in Devin Desktop and CLI.
The description reports a 50.0% result on FrontierCode 1.1 Main.
The description reports 58% fewer turns, 81% lower cost, and a higher score than SWE-1.7.
The description states that SWE-2 is 64% less expensive than Fable 5.1 and costs one quarter as much as GPT-6 Astra.