Model comparison
GPT-5.2 Codex vs o1
GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 40.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in agentic & tool use, where GPT-5.2 Codex leads 41.0 to 24.6.
- GPT-5.2 Codex is cheaper at $1.75 / $14 per million input/output tokens, against $15 / $60 for o1.
- GPT-5.2 Codex accepts more context: 400K tokens versus 200K.
Side by side
| GPT-5.2 Codex | o1 | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 42.6 | 40.9 |
| Released | 2025-12-18 | 2024-09-12 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 200K |
| Max output | 128K | 100K |
| Input $ / M tokens | $1.75 | $15 |
| Output $ / M tokens | $14 | $60 |
| Results tracked | 5 | 52 |
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Category by category
Coding Too close to call
GPT-5.2 Codex: 45.5 (#71), o1: 46.1 (#70)
| Benchmark | GPT-5.2 Codex | o1 |
|---|---|---|
| SWE-bench Verified (bash only) | 72.8% | — |
| Aider Polyglot | — | 61.7% |
| LMArena WebDev | 1339 | — |
| SWE-bench Multilingual | 66.3% | — |
| WeirdML | — | 47.6% |
| LiveBench Coding | — | 69.7% |
| LMArena Coding | — | 1367 |
| CadEval | — | 56% |
| ALE-Bench | 1,300 | — |
| HumanEval+ | — | 89% |
| MBPP+ | — | 80.2% |
Agentic & Tool Use GPT-5.2 Codex leads
GPT-5.2 Codex: 41.0 (#22), o1: 24.6 (#117)
| Benchmark | GPT-5.2 Codex | o1 |
|---|---|---|
| Terminal-Bench | 66.5% | — |
| Cybench | — | 10% |
| METR Time Horizons | — | 51.1% |
Reasoning Not comparable
GPT-5.2 Codex: —, o1: 27.9 (#111)
| Benchmark | GPT-5.2 Codex | o1 |
|---|---|---|
| SimpleBench | — | 41.7% |
| ARC-AGI-1 | — | 30.7% |
| Chess Puzzles | — | 15% |
| EnigmaEval | — | 5.7% |
| LiveBench Reasoning | — | 91.6% |
| LMArena Hard Prompts | — | 1371 |
| DTBench | — | 74.7% |
| LiveBench Data Analysis | — | 65.5% |
| LMCA | — | 22.3% |
| Epoch Capabilities Index | — | 141.91 |
| LiveBench | — | 75.7% |
Math Not comparable
GPT-5.2 Codex: —, o1: 36.1 (#175)
| Benchmark | GPT-5.2 Codex | o1 |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 14.7% |
| OTIS Mock AIME 2024-2025 | — | 73.3% |
| LiveBench Math | — | 80.3% |
| LMArena Math | — | 1388 |
| MATH Level 5 | — | 94.7% |
| FrontierMath (Feb 2025 set) | — | 9.3% |
Knowledge Not comparable
GPT-5.2 Codex: —, o1: 41.5 (#110)
| Benchmark | GPT-5.2 Codex | o1 |
|---|---|---|
| GPQA Diamond | — | 76.8% |
| Humanity's Last Exam | — | 8% |
| SimpleQA Verified | — | 41.1% |
| Confabulations | — | 11.7% |
| LMArena Expert | — | 1361 |
Multimodal Not comparable
GPT-5.2 Codex: —, o1: 34.2 (#93)
| Benchmark | GPT-5.2 Codex | o1 |
|---|---|---|
| LMArena Vision | — | 1168 |
| GeoBench | — | 80% |
| VPCT | — | 37% |
| SpatialViz-Bench | — | 41.4% |
Multilingual Not comparable
GPT-5.2 Codex: —, o1: 48.6 (#142)
| Benchmark | GPT-5.2 Codex | o1 |
|---|---|---|
| LMArena Non-English | — | 1358 |
| LMArena Chinese | — | 1394 |
| LMArena French | — | 1344 |
| LMArena German | — | 1337 |
| LMArena Japanese | — | 1346 |
| LMArena Korean | — | 1396 |
| LMArena Russian | — | 1356 |
| LMArena Spanish | — | 1345 |
Instruction Following Not comparable
GPT-5.2 Codex: —, o1: 74.8 (#86)
| Benchmark | GPT-5.2 Codex | o1 |
|---|---|---|
| LiveBench Instruction Following | — | 81.5% |
| LMArena Instruction Following | — | 1367 |
Long Context Not comparable
GPT-5.2 Codex: —, o1: 50.3 (#9)
| Benchmark | GPT-5.2 Codex | o1 |
|---|---|---|
| Fiction.LiveBench | — | 83.3% |
| LMArena Longer Query | — | 1378 |
Writing & Preference Not comparable
GPT-5.2 Codex: —, o1: 55.6 (#144)
| Benchmark | GPT-5.2 Codex | o1 |
|---|---|---|
| LMArena Text | — | 1366 |
| LMArena Creative Writing | — | 1348 |
| Short-Story Creative Writing | — | 70.2% |
| LMArena Multi-Turn | — | 1369 |
| LiveBench Language | — | 65.4% |
Frequently asked questions
Is GPT-5.2 Codex better than o1?
GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 40.9 on the Noometry Index.
Which is cheaper, GPT-5.2 Codex or o1?
GPT-5.2 Codex is cheaper. It lists at $1.75 per million input tokens and $14 per million output tokens; o1 lists at $15 and $60.
Is GPT-5.2 Codex or o1 better for coding?
They score almost the same on coding (45.5 vs 46.1); test both on your own repository before choosing.
Which has the bigger context window?
GPT-5.2 Codex does, with 400K tokens against 200K.
How many benchmarks do GPT-5.2 Codex and o1 share?
0 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and o1 has 52.