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SWE-2

CognitionProprietary

描述

SWE-2 is Cognition's most advanced coding model, post-trained from Moonshot AI's 2.8-trillion-parameter Kimi K3 with reinforcement learning scaled to the multi-trillion-parameter regime for the first time. A single RL run trains all reasoning-effort levels (medium, high, max) together with per-effort cost penalties tuned to the base model's Pareto frontier, advancing the whole cost-performance curve rather than a single operating point. On FrontierCode 1.1 Main it scores 50.0%, within one point of Claude Fable 5.1 (50.9%) while Cognition states it is 64% cheaper; on DeepSWE 1.1 it scores 73.0%; on Terminal-Bench 2.1 it scores 92.8%; on Terminal-Bench 4.0 it scores 27.3%. SWE-2 is available starting 2026-09-10 in Devin Desktop and Devin CLI, with Devin Web and Fusion rollout in progress; Cognition has not published a standalone public API, model card, or context-window specification independent of the Devin product.

發布日期
2026-09-10
參數規模
—
上下文長度
—
支援模態
—

能力雷達圖

60
general
60
coding
60
reasoning
51
science估算
60
agents
0
multimodal

缺少專門科學評測時,Science 由 LLM Stats 科學得分或推理能力估算。

排行榜排名

暫無排名資料

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Code

DeepSWE 1.173.0%自報

Reasoning

Terminal-Bench 2.192.8%自報
FrontierCode 1.150.0%自報
Terminal-Bench 4.027.3%自報

AA 評測指數

(Artificial Analysis)

暫無 AA 評測資料

LLM Stats 分類評分

(LLM Stats (zeroeval))
Reasoning
60
General
60
Agents
60
Code
60
Tool Calling
60

定價

暫無定價資料

速度

暫無速度資料

供應商價格排行

暫無提供商資料

外部連結