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SWE-check

CognitionProprietaryPending Human Review

SWE-check is a specialized bug-detection language model developed by Cognition with Applied Compute and first made available in the Windsurf Next public preview. It analyzes a change diff, investigates the surrounding code, and produces structured bug descriptions and fixes for display in the editor. Reinforcement learning first builds task capability, then tunes latency and product behavior using a separate alignment phase. This is a distinct trained generative review model rather than a generic code-review feature or binary decision endpoint. Architecture, parameter counts, and model context limits remain undisclosed. Its reported parity with frontier models applies to internal in-distribution evaluations, with a remaining gap on out-of-distribution tasks.

2026-04-14
Undisclosed
Proprietary

Specifications

Architecture
Undisclosed
License
Proprietary
Type
text
Modalities
text

Benchmark Scores

Advanced Specifications

Model Family
SWE
API Access
Not Available
Chat Interface
Not Available
Variants
Windsurf Next preview

Capabilities & Limitations

Capabilities
bug detectionstructured review outputtool usecode analysis
Known Limitations
Published results show a gap on out-of-distribution bugsInternal F1 comparisons are not universal bug-detection accuracyAvailability was initially Windsurf Next preview; no standalone inference API verified
Notable Use Cases
instant diff reviewfinding regressionssuggesting bug fixes
Tool Use Support
Yes

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