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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.

發布日期
2026-11-04
參數規模
276.0B
上下文長度
—
支援模態
—

能力雷達圖

50
general
50
coding
40
reasoning
34
science估算
50
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 1.160.1%自報
SWE Atlas - Codebase QnA50.0%自報
ExploitBench34.8%自報

Reasoning

Terminal-Bench 2.189.2%自報
FrontierCode 1.145.5%自報
FrontierCode 2.024.0%自報
Terminal-Bench 4.020.0%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))
General
50
Agents
50
Code
50
Tool Calling
50
Reasoning
40
Safety
30

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