Model comparison
Claude 3 Haiku vs GPT-5.1
GPT-5.1 is the stronger model overall, scoring 48.8 to 25.7 on the Noometry Index.
Last verified . 25 shared benchmarks.
Summary
- They share 25 benchmarks with published results for both. Claude 3 Haiku scores higher in 0 categories and GPT-5.1 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.1 leads 50.3 to 9.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.8% for Claude 3 Haiku and 88.6% for GPT-5.1.
Side by side
| Claude 3 Haiku | GPT-5.1 | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 25.7 | 48.8 |
| Released | 2024-03-07 | 2025-11-13 |
| Weights | Proprietary | Proprietary |
| Context window | — | 400K |
| Max output | — | 128K |
| Input $ / M tokens | — | $1.25 |
| Output $ / M tokens | — | $10 |
| Results tracked | 37 | 63 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5.1 leads
Claude 3 Haiku: 26.1 (#320), GPT-5.1: 46.9 (#59)
| Benchmark | Claude 3 Haiku | GPT-5.1 |
|---|---|---|
| WeirdML | 9.8% | 60.8% |
| LMArena Coding | 1199 | 1454 |
| SWE-bench Verified | — | 68% |
| SWE-bench Verified (bash only) | — | 66% |
| LMArena WebDev | — | 1395 |
| SciCode | — | 43.3% |
| GSO | — | 13.7% |
| BigCodeBench Instruct | 39.4% | — |
| LiveBench Coding | — | 72.5% |
| BigCodeBench Complete | 50.1% | — |
| CadEval | 12% | — |
| ALE-Bench | — | 1,192 |
| HumanEval+ | 68.9% | — |
| MBPP+ | 68.8% | — |
Agentic & Tool Use Not comparable
Claude 3 Haiku: —, GPT-5.1: 32.5 (#55)
| Benchmark | Claude 3 Haiku | GPT-5.1 |
|---|---|---|
| Terminal-Bench | — | 47.6% |
| DeepResearch Bench | — | 42.8% |
| LMArena Search | — | 1199 |
| Vending-Bench 2 | — | 1,473 |
Reasoning GPT-5.1 leads
Claude 3 Haiku: 15.7 (#303), GPT-5.1: 39.9 (#50)
| Benchmark | Claude 3 Haiku | GPT-5.1 |
|---|---|---|
| LMArena Hard Prompts | 1174 | 1457 |
| DTBench | 50.1% | 90.1% |
| LMCA | 8.8% | 43.9% |
| Epoch Capabilities Index | 118.3 | 149.66 |
| ForecastBench | 53.2 | 58.1 |
| ARC-AGI-2 | — | 17.6% |
| SimpleBench | — | 53.2% |
| Kagi LLM Benchmark | 34.2% | — |
| ARC-AGI-1 | — | 72.8% |
| CritPt | — | 4.9% |
| Chess Puzzles | — | 32% |
| EnigmaEval | — | 11.2% |
| LiveBench Reasoning | — | 95.8% |
| Mystery Game Puzzles | — | 19% |
| LiveBench Data Analysis | — | 72.1% |
| LiveBench | — | 78.8% |
| WinoGrande | 74.2% | — |
Math GPT-5.1 leads
Claude 3 Haiku: 9.2 (#313), GPT-5.1: 50.3 (#45)
| Benchmark | Claude 3 Haiku | GPT-5.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.8% | 88.6% |
| LMArena Math | 1188 | 1446 |
| Omni-MATH | — | 46.4% |
| LiveBench Math | — | 94.5% |
| MATH Level 5 | 14.9% | — |
| FrontierMath (Feb 2025 set) | — | 31% |
| FrontierMath Tier 4 (v1) | — | 12.5% |
Knowledge GPT-5.1 leads
Claude 3 Haiku: 17.3 (#280), GPT-5.1: 50.5 (#65)
| Benchmark | Claude 3 Haiku | GPT-5.1 |
|---|---|---|
| GPQA Diamond | 36.3% | 87.6% |
| LMArena Expert | 1148 | 1470 |
| Humanity's Last Exam | — | 23.7% |
| SimpleQA Verified | — | 48% |
| MMLU-Pro | — | 57.9% |
| Confabulations | 34.2% | — |
| Vectara Hallucination Rate | — | 10.9% |
| GPQA (HELM) | — | 44.2% |
| MMLU | 73.8% | — |
Multimodal GPT-5.1 leads
Claude 3 Haiku: 23.1 (#123), GPT-5.1: 44.0 (#17)
| Benchmark | Claude 3 Haiku | GPT-5.1 |
|---|---|---|
| LMArena Vision | 950 | 1250 |
| VPCT | — | 58.7% |
| LMArena Document | — | 1403 |
| ScienceQA | 72% | — |
Multilingual GPT-5.1 leads
Claude 3 Haiku: 36.1 (#238), GPT-5.1: 54.0 (#51)
| Benchmark | Claude 3 Haiku | GPT-5.1 |
|---|---|---|
| LMArena Non-English | 1178 | 1431 |
| LMArena Chinese | 1155 | 1495 |
| LMArena French | 1194 | 1451 |
| LMArena German | 1174 | 1439 |
| LMArena Japanese | 1102 | 1453 |
| LMArena Korean | 1108 | 1401 |
| LMArena Russian | 1204 | 1435 |
| LMArena Spanish | 1165 | 1430 |
Instruction Following GPT-5.1 leads
Claude 3 Haiku: 61.5 (#242), GPT-5.1: 84.0 (#1)
| Benchmark | Claude 3 Haiku | GPT-5.1 |
|---|---|---|
| LMArena Instruction Following | 1174 | 1442 |
| LiveBench Instruction Following | — | 93.3% |
| IFEval | — | 93.5% |
Long Context GPT-5.1 leads
Claude 3 Haiku: 36.1 (#232), GPT-5.1: 47.6 (#14)
| Benchmark | Claude 3 Haiku | GPT-5.1 |
|---|---|---|
| LMArena Longer Query | 1191 | 1448 |
| CL-bench | — | 23.7% |
| CL-bench Life | — | 17.3% |
Writing & Preference GPT-5.1 leads
Claude 3 Haiku: 29.8 (#286), GPT-5.1: 64.7 (#53)
| Benchmark | Claude 3 Haiku | GPT-5.1 |
|---|---|---|
| LMArena Text | 1195 | 1443 |
| LMArena Creative Writing | 1157 | 1427 |
| LMArena Multi-Turn | 1190 | 1449 |
| EQ-Bench Creative Writing | 717 | — |
| WildBench | — | 86.3% |
| LiveBench Language | — | 80.2% |
Frequently asked questions
Is Claude 3 Haiku better than GPT-5.1?
GPT-5.1 is the stronger model overall, scoring 48.8 to 25.7 on the Noometry Index.
Is Claude 3 Haiku or GPT-5.1 better for coding?
GPT-5.1 scores higher on coding benchmarks: 46.9 versus 26.1 in the Noometry coding category.
How many benchmarks do Claude 3 Haiku and GPT-5.1 share?
25 benchmarks have published results for both models. Claude 3 Haiku has 37 scored results on Noometry and GPT-5.1 has 63.