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SWE-2

CognitionProprietary

설명

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.

출시일
2026-09-10
파라미터
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컨텍스트 길이
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모달리티
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능력 레이더

60
general
60
coding
60
reasoning
51
science추정
60
agents
0
multimodal

전용 과학 벤치마크가 없을 때 Science는 LLM Stats 과학 점수 또는 추론 능력에서 추정합니다.

랭킹

랭킹 데이터가 없습니다

벤치마크 점수 (LLM Stats)

(LLM Stats (zeroeval))

Code

DeepSWE 1.173.0%자체 보고

Reasoning

Terminal-Bench 2.192.8%자체 보고
FrontierCode 1.150.0%자체 보고
Terminal-Bench 4.027.3%자체 보고

AA 평가 지수

(Artificial Analysis)

AA 평가 데이터가 없습니다

LLM Stats 카테고리 점수

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

가격

가격 데이터가 없습니다

속도

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공급자 가격 순위

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