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SWE-2 Flash

CognitionProprietary

描述

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.

发布日期
2026-11-04
参数规模
276.0B
上下文长度
—
支持模态
—

能力雷达图

50
general
50
coding
40
reasoning
34
science估算
50
agents
0
multimodal

缺少专门科学评测时,Science 由 LLM Stats 科学得分或推理能力估算。

排行榜排名

暂无排名数据

基准测试分数 (LLM Stats)

(LLM Stats (zeroeval))

Code

DeepSWE 1.160.1%自报
SWE Atlas - Codebase QnA50.0%自报
ExploitBench34.8%自报

Reasoning

Terminal-Bench 2.189.2%自报
FrontierCode 1.145.5%自报
FrontierCode 2.024.0%自报
Terminal-Bench 4.020.0%自报

AA 评测指数

(Artificial Analysis)

暂无 AA 评测数据

LLM Stats 分类评分

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

定价

暂无定价数据

速度

暂无速度数据

供应商价格排行

暂无提供商数据

外部链接