DeepSWE-Preview: benchmark scores, price and ranking
DeepSWE-Preview ranks #334 of 743 LLMs on the LLMs Tiger aggregate benchmark score (48.6), based on 1 benchmark results captured up to 2026-10-13.
- Type
- Preview release
- Open weights
- No
- Aggregate rank
- #334 of 743 (score 48.6)
Across the 1 benchmark where at least ten models are scored, DeepSWE-Preview is in the top 10% on 0 and in the top half on 0.
DeepSWE-Preview benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| SWE-bench Verified | 42.2% | #50 of 73 | SWE-bench Verified leaderboard | 2026-10-13 |
About DeepSWE-Preview
DeepSWE-Preview is a preview release. No API price is listed for it yet. We hold 1 benchmark result for it across 1 area, and none is in the top tenth of its board.
Where DeepSWE-Preview stands
On our aggregate score, DeepSWE-Preview is #334 of 743 ranked models, around the middle of the table. Its score is 48.6; the scale is centred on 50, so it sits 1.4 points below the typical model. That beats 55% of the ranked field.
DeepSWE-Preview, benchmark by benchmark
DeepSWE-Preview lands below the middle on SWE-bench Verified: 42.2%, #50 of 73, with 67% of the field scoring higher. Claude Opus 4.7 (max) leads at 83.5%; the closest result above is Amazon.nova Premier v1:0 at 42.4%. It covers real GitHub issues resolved. The board median is 56.4%, so DeepSWE-Preview is 14.2 points below it. Source: SWE-bench Verified leaderboard, captured 2026-10-13.
Reading these numbers
The 1 score on this page comes from 1 source: SWE-bench Verified leaderboard (1). No official leaderboard supplied any of them, so treat them as third-party measurements. With 1 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #331 gemini-1.5-flash-exp-0827 (48.7)
- #332 grok-4.20-beta-0309-reasoning (48.7)
- #333 qwen3-4b-instruct-2507 (48.7)
- #335 chatgpt-4o-latest (2025-02-15) (48.6)
- #336 Nemotron-H-56B-Base-8K (48.6)
- #337 Llama3-SWE-RL-70B (48.6)
Compare it on the live leaderboard → · How the aggregate score works