Model card
GPT-5.2.
OpenAIapiUndisclosed params
§ 01 · Benchmarks
Every benchmark GPT-5.2 has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | SWE-Bench | Computer Code · Code Generation | resolve-rate-agentic | 80.0% | #4 | 2026-02-01 | source ↗ |
| 02 | SWE-Bench | Computer Code · Code Generation | resolve-rate | 80.0% | #6 | 2026-02-01 | source ↗ |
| 03 | SWE-bench Verified | Agentic AI · SWE-bench | resolve-rate | 80.0% | #6 | — | source ↗ |
| 04 | MMLU-Pro | Reasoning · Commonsense Reasoning | accuracy | 87.4% | #10 | 2026-04-20 | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 02 · Strengths by area
Where GPT-5.2 actually performs.
§ 03 · Papers
1 paper with results for GPT-5.2.
- 2023-10-10· Computer Code· 1 result
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao et al.
§ 04 · Related models
Other OpenAI models scored on Codesota.
§ 05 · Sources & freshness
Where these numbers come from.
openai-internal
1
result
swebench-leaderboard
1
result
editorial
1
result
pricepertoken
1
result
3 of 4 rows marked verified. · first result 2026-02-01, latest 2026-04-20.