SWE-check
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.
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