Model comparison
Claude 3 Haiku vs GPT-5.5
GPT-5.5 is the stronger model overall, scoring 63.4 to 25.7 on the Noometry Index.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. Claude 3 Haiku scores higher in 0 categories and GPT-5.5 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.5 leads 81.5 to 9.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.8% for Claude 3 Haiku and 100% for GPT-5.5.
Side by side
| Claude 3 Haiku | GPT-5.5 | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 25.7 | 63.4 |
| Released | 2024-03-07 | 2026-04-23 |
| Weights | Proprietary | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 128K |
| Input $ / M tokens | — | $5 |
| Output $ / M tokens | — | $30 |
| Results tracked | 37 | 71 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5.5 leads
Claude 3 Haiku: 26.1 (#320), GPT-5.5: 58.3 (#13)
| Benchmark | Claude 3 Haiku | GPT-5.5 |
|---|---|---|
| WeirdML | 9.8% | 84.9% |
| LMArena Coding | 1199 | 1494 |
| SWE-bench Verified | — | 80.6% |
| DeepSWE | — | 67% |
| FrontierCode | — | 43% |
| LMArena WebDev | — | 1512 |
| SciCode | — | 56.1% |
| GSO | — | 40.2% |
| BigCodeBench Instruct | 39.4% | — |
| MirrorCode | — | 10% |
| BigCodeBench Complete | 50.1% | — |
| CadEval | 12% | — |
| ALE-Bench | — | 1,943 |
| HumanEval+ | 68.9% | — |
| MBPP+ | 68.8% | — |
Agentic & Tool Use Not comparable
Claude 3 Haiku: —, GPT-5.5: 50.7 (#6)
| Benchmark | Claude 3 Haiku | GPT-5.5 |
|---|---|---|
| Terminal-Bench | — | 84.7% |
| APEX-Agents | — | 55.1% |
| OSWorld 2.0 | — | 13% |
| Remote Labor Index | — | 6.3% |
| τ²-bench Banking | — | 44.6% |
| DeepResearch Bench | — | 54% |
| PostTrainBench | — | 27.2% |
| ExploitBench | — | 47.4% |
| GBAEval | — | 53.2% |
| GDP.pdf | — | 26% |
| LMArena Search | — | 1242 |
| Vending-Bench 2 | — | 7,524 |
Reasoning GPT-5.5 leads
Claude 3 Haiku: 15.7 (#303), GPT-5.5: 72.7 (#8)
| Benchmark | Claude 3 Haiku | GPT-5.5 |
|---|---|---|
| Kagi LLM Benchmark | 34.2% | 88.8% |
| LMArena Hard Prompts | 1174 | 1489 |
| DTBench | 50.1% | 96% |
| LMCA | 8.8% | 54.3% |
| Epoch Capabilities Index | 118.3 | 159.25 |
| ForecastBench | 53.2 | 60.6 |
| ARC-AGI-2 | — | 85% |
| SimpleBench | — | 69% |
| NYT Connections (extended) | — | 96.2% |
| ARC-AGI-1 | — | 95% |
| CritPt | — | 27.1% |
| Chess Puzzles | — | 54% |
| EBR-Bench | — | 34.3% |
| Mystery Game Puzzles | — | 56% |
| Surface Evolver Bench | — | 88.1% |
| Bench to the Future 3 | — | 0.14 |
| WinoGrande | 74.2% | — |
Math GPT-5.5 leads
Claude 3 Haiku: 9.2 (#313), GPT-5.5: 81.5 (#9)
| Benchmark | Claude 3 Haiku | GPT-5.5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.8% | 100% |
| LMArena Math | 1188 | 1486 |
| FrontierMath (Tiers 1-3) | — | 85.3% |
| FrontierMath Tier 4 | — | 72.5% |
| MathArena Final-Answer Competitions | — | 94.3% |
| ProofBench | — | 50% |
| MATH Level 5 | 14.9% | — |
| FrontierMath (Feb 2025 set) | — | 51.7% |
| FrontierMath Erdős | — | 0% |
| FrontierMath Tier 4 (v1) | — | 35.4% |
Knowledge GPT-5.5 leads
Claude 3 Haiku: 17.3 (#280), GPT-5.5: 64.4 (#14)
| Benchmark | Claude 3 Haiku | GPT-5.5 |
|---|---|---|
| GPQA Diamond | 36.3% | 94% |
| LMArena Expert | 1148 | 1508 |
| SimpleQA Verified | — | 63% |
| Confabulations | 34.2% | — |
| Vectara Hallucination Rate | — | 9.3% |
| MMLU | 73.8% | — |
Multimodal GPT-5.5 leads
Claude 3 Haiku: 23.1 (#123), GPT-5.5: 47.1 (#11)
| Benchmark | Claude 3 Haiku | GPT-5.5 |
|---|---|---|
| LMArena Vision | 950 | 1297 |
| Blueprint-Bench 2 | — | 36.2% |
| Furniture Assembly | — | 44.2% |
| LMArena Document | — | 1486 |
| ScienceQA | 72% | — |
Multilingual GPT-5.5 leads
Claude 3 Haiku: 36.1 (#238), GPT-5.5: 56.5 (#19)
| Benchmark | Claude 3 Haiku | GPT-5.5 |
|---|---|---|
| LMArena Non-English | 1178 | 1467 |
| LMArena Chinese | 1155 | 1535 |
| LMArena French | 1194 | 1486 |
| LMArena German | 1174 | 1478 |
| LMArena Japanese | 1102 | 1498 |
| LMArena Korean | 1108 | 1461 |
| LMArena Russian | 1204 | 1473 |
| LMArena Spanish | 1165 | 1469 |
Instruction Following GPT-5.5 leads
Claude 3 Haiku: 61.5 (#242), GPT-5.5: 77.7 (#18)
| Benchmark | Claude 3 Haiku | GPT-5.5 |
|---|---|---|
| LMArena Instruction Following | 1174 | 1479 |
Long Context GPT-5.5 leads
Claude 3 Haiku: 36.1 (#232), GPT-5.5: 48.3 (#12)
| Benchmark | Claude 3 Haiku | GPT-5.5 |
|---|---|---|
| LMArena Longer Query | 1191 | 1484 |
| CL-bench Life | — | 22.2% |
Writing & Preference GPT-5.5 leads
Claude 3 Haiku: 29.8 (#286), GPT-5.5: 72.8 (#13)
| Benchmark | Claude 3 Haiku | GPT-5.5 |
|---|---|---|
| LMArena Text | 1195 | 1471 |
| LMArena Creative Writing | 1157 | 1455 |
| EQ-Bench Creative Writing | 717 | 1844 |
| LMArena Multi-Turn | 1190 | 1477 |
| EQ-Bench 4 | — | 1315 |
Frequently asked questions
Is Claude 3 Haiku better than GPT-5.5?
GPT-5.5 is the stronger model overall, scoring 63.4 to 25.7 on the Noometry Index.
Is Claude 3 Haiku or GPT-5.5 better for coding?
GPT-5.5 scores higher on coding benchmarks: 58.3 versus 26.1 in the Noometry coding category.
How many benchmarks do Claude 3 Haiku and GPT-5.5 share?
27 benchmarks have published results for both models. Claude 3 Haiku has 37 scored results on Noometry and GPT-5.5 has 71.