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SWE-2 Flash

CognitionProprietary

설명

SWE-2 Flash is Cognition's fast, low-cost coding model, built on Thinking Machines' Inkling-Small (276B total / 12B active parameters) with a large-scale mid-training stage (a few trillion tokens of scientific articles, blogs, code and other sources, in three stages) followed by large-scale reinforcement learning on higher-quality, more diverse task types. Cognition reports 24.0% on FrontierCode 2.0, 45.5% on FrontierCode 1.1 Main, 60.1% on DeepSWE 1.1, 20.0% on Terminal-Bench 4.0 and 89.2% on Terminal-Bench 2.1, and states it outperforms all American open-weight models. Training targeted cybersecurity work (ExploitBench 34.8%, up from 11.3% for the base model). It is available starting 2026-11-04 in Devin Desktop and Devin CLI (free through 2026-11-30) at one-fifth the price and about 3x the generation speed (roughly 200 vs 60 tokens/s) of SWE-2. Weights are not public; Cognition plans a program to share them with trusted industry partners and researchers. No standalone public API, per-token pricing, or context-window specification has been published.

출시일
2026-11-04
파라미터
276.0B
컨텍스트 길이
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모달리티
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능력 레이더

50
general
50
coding
40
reasoning
34
science추정
50
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 1.160.1%자체 보고
SWE Atlas - Codebase QnA50.0%자체 보고
ExploitBench34.8%자체 보고

Reasoning

Terminal-Bench 2.189.2%자체 보고
FrontierCode 1.145.5%자체 보고
FrontierCode 2.024.0%자체 보고
Terminal-Bench 4.020.0%자체 보고

AA 평가 지수

(Artificial Analysis)

AA 평가 데이터가 없습니다

LLM Stats 카테고리 점수

(LLM Stats (zeroeval))
General
50
Agents
50
Code
50
Tool Calling
50
Reasoning
40
Safety
30

가격

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속도

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공급자 가격 순위

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