Model comparison
GPT-5.1 vs o3
GPT-5.1 is the stronger model overall, scoring 49.0 to 47.5 on the Noometry Index.
Last verified . 49 shared benchmarks.
Summary
- They share 49 benchmarks with published results for both. GPT-5.1 scores higher in 6 categories and o3 in 4 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in instruction following, where GPT-5.1 leads 83.9 to 72.8.
- The biggest single-benchmark swing is GPQA (HELM): 44.2% for GPT-5.1 and 75.3% for o3.
- Both cost about the same: $1.25 input and $10 output per million tokens.
- GPT-5.1 accepts more context: 400K tokens versus 200K.
Side by side
| GPT-5.1 | o3 | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 49.0 | 47.5 |
| Released | 2025-11-13 | 2025-04-16 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 200K |
| Max output | 128K | 100K |
| Input $ / M tokens | $1.25 | $2 |
| Output $ / M tokens | $10 | $8 |
| Results tracked | 63 | 63 |
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Category by category
Coding Too close to call
GPT-5.1: 46.4 (#66), o3: 46.8 (#64)
| Benchmark | GPT-5.1 | o3 |
|---|---|---|
| SWE-bench Verified | 68% | 62.3% |
| SWE-bench Verified (bash only) | 66% | 58.4% |
| GSO | 13.7% | 8.8% |
| WeirdML | 60.8% | 52.4% |
| LMArena Coding | 1454 | 1408 |
| ALE-Bench | 1,192 | 933.55 |
| Aider Polyglot | — | 81.3% |
| LMArena WebDev | 1395 | — |
| SciCode | 43.3% | — |
| LiveBench Coding | 72.5% | — |
| CadEval | — | 74% |
Agentic & Tool Use o3 leads
GPT-5.1: 32.7 (#60), o3: 34.5 (#44)
| Benchmark | GPT-5.1 | o3 |
|---|---|---|
| DeepResearch Bench | 42.8% | 45.2% |
| LMArena Search | 1199 | 1144 |
| Terminal-Bench | 47.6% | — |
| Berkeley Function Calling Leaderboard | — | 63% |
| GDPval | — | 30.8% |
| OSWorld | — | 23% |
| METR Time Horizons | — | 65.4% |
| Vending-Bench 2 | 1,473 | — |
Reasoning GPT-5.1 leads
GPT-5.1: 39.8 (#58), o3: 32.0 (#78)
| Benchmark | GPT-5.1 | o3 |
|---|---|---|
| ARC-AGI-2 | 17.6% | 6.5% |
| SimpleBench | 53.2% | 53.1% |
| ARC-AGI-1 | 72.8% | 60.8% |
| CritPt | 4.9% | 1.4% |
| Chess Puzzles | 32% | 38% |
| EnigmaEval | 11.2% | 13.1% |
| LMArena Hard Prompts | 1457 | 1402 |
| Mystery Game Puzzles | 19% | 29% |
| DTBench | 90.1% | 84.8% |
| LMCA | 43.9% | 39.7% |
| Epoch Capabilities Index | 149.64 | 146.86 |
| ForecastBench | 58.1 | 62.5 |
| Kagi LLM Benchmark | — | 67.6% |
| LiveBench Reasoning | 95.8% | — |
| LiveBench Data Analysis | 72.1% | — |
| LiveBench | 78.8% | — |
Math GPT-5.1 leads
GPT-5.1: 52.2 (#51), o3: 50.2 (#58)
| Benchmark | GPT-5.1 | o3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.6% | 84.4% |
| Omni-MATH | 46.4% | 71.4% |
| LMArena Math | 1447 | 1426 |
| FrontierMath (Feb 2025 set) | 31% | 18.7% |
| FrontierMath Tier 4 (v1) | 12.5% | 2.1% |
| FrontierMath (Tiers 1-3) | — | 33.3% |
| LiveBench Math | 94.5% | — |
| MATH Level 5 | — | 97.8% |
Knowledge o3 leads
GPT-5.1: 50.6 (#71), o3: 54.6 (#52)
| Benchmark | GPT-5.1 | o3 |
|---|---|---|
| GPQA Diamond | 87.6% | 81.8% |
| Humanity's Last Exam | 23.7% | 20.3% |
| SimpleQA Verified | 48% | 49.4% |
| MMLU-Pro | 57.9% | 85.9% |
| GPQA (HELM) | 44.2% | 75.3% |
| LMArena Expert | 1470 | 1402 |
| Confabulations | — | 14.4% |
| Vectara Hallucination Rate | 10.9% | — |
Multimodal GPT-5.1 leads
GPT-5.1: 44.8 (#19), o3: 41.4 (#36)
| Benchmark | GPT-5.1 | o3 |
|---|---|---|
| LMArena Vision | 1250 | 1214 |
| VPCT | 58.7% | 52% |
| GeoBench | — | 74% |
| LMArena Document | 1403 | — |
Multilingual GPT-5.1 leads
GPT-5.1: 53.8 (#56), o3: 51.7 (#105)
| Benchmark | GPT-5.1 | o3 |
|---|---|---|
| LMArena Non-English | 1431 | 1401 |
| LMArena Chinese | 1495 | 1437 |
| LMArena French | 1450 | 1430 |
| LMArena German | 1438 | 1420 |
| LMArena Japanese | 1453 | 1403 |
| LMArena Korean | 1401 | 1370 |
| LMArena Russian | 1435 | 1406 |
| LMArena Spanish | 1433 | 1395 |
Instruction Following GPT-5.1 leads
GPT-5.1: 83.9 (#1), o3: 72.8 (#127)
| Benchmark | GPT-5.1 | o3 |
|---|---|---|
| IFEval | 93.5% | 86.9% |
| LMArena Instruction Following | 1443 | 1368 |
| LiveBench Instruction Following | 93.3% | — |
Long Context o3 leads
GPT-5.1: 47.6 (#14), o3: 53.3 (#6)
| Benchmark | GPT-5.1 | o3 |
|---|---|---|
| CL-bench | 23.7% | 17.8% |
| LMArena Longer Query | 1447 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench Life | 17.3% | — |
Writing & Preference GPT-5.1 leads
GPT-5.1: 64.5 (#55), o3: 63.5 (#64)
| Benchmark | GPT-5.1 | o3 |
|---|---|---|
| LMArena Text | 1443 | 1410 |
| LMArena Creative Writing | 1427 | 1359 |
| WildBench | 86.3% | 86.1% |
| LMArena Multi-Turn | 1450 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| EQ-Bench Creative Writing | — | 1676 |
| LiveBench Language | 80.2% | — |
Frequently asked questions
Is GPT-5.1 better than o3?
GPT-5.1 is the stronger model overall, scoring 49.0 to 47.5 on the Noometry Index.
Which is cheaper, GPT-5.1 or o3?
GPT-5.1 is cheaper. It lists at $1.25 per million input tokens and $10 per million output tokens; o3 lists at $2 and $8.
Is GPT-5.1 or o3 better for coding?
They score almost the same on coding (46.4 vs 46.8); test both on your own repository before choosing.
Which has the bigger context window?
GPT-5.1 does, with 400K tokens against 200K.
How many benchmarks do GPT-5.1 and o3 share?
49 benchmarks have published results for both models. GPT-5.1 has 63 scored results on Noometry and o3 has 63.