Model comparison
Claude Haiku 4.5 vs GPT-5.5
GPT-5.5 is the stronger model overall, scoring 63.4 to 39.3 on the Noometry Index. Claude Haiku 4.5 costs 5.6× less per token, which makes it the better buy when GPT-5.5's lead doesn't matter for your workload.
Last verified . 43 shared benchmarks.
Summary
- They share 43 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 0 categories and GPT-5.5 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.5 leads 72.7 to 15.1.
- The biggest single-benchmark swing is NYT Connections (extended): 14.3% for Claude Haiku 4.5 and 96.2% for GPT-5.5.
- Claude Haiku 4.5 is cheaper at $1 / $5 per million input/output tokens, against $5 / $30 for GPT-5.5.
- GPT-5.5 accepts more context: 1.05M tokens versus 200K.
Side by side
| Claude Haiku 4.5 | GPT-5.5 | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 39.3 | 63.4 |
| Released | 2025-10-15 | 2026-04-23 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 1.05M |
| Max output | 64K | 128K |
| Input $ / M tokens | $1 | $5 |
| Output $ / M tokens | $5 | $30 |
| Results tracked | 53 | 71 |
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Category by category
Coding GPT-5.5 leads
Claude Haiku 4.5: 43.9 (#71), GPT-5.5: 58.3 (#13)
| Benchmark | Claude Haiku 4.5 | GPT-5.5 |
|---|---|---|
| LMArena WebDev | 1330 | 1512 |
| SciCode | 43.3% | 56.1% |
| WeirdML | 45.4% | 84.9% |
| LMArena Coding | 1454 | 1494 |
| ALE-Bench | 653.48 | 1,943 |
| SWE-bench Verified | — | 80.6% |
| DeepSWE | — | 67% |
| FrontierCode | — | 43% |
| SWE-bench Verified (bash only) | 66.6% | — |
| SWE-bench Multilingual | 64.7% | — |
| GSO | — | 40.2% |
| MirrorCode | — | 10% |
Agentic & Tool Use GPT-5.5 leads
Claude Haiku 4.5: 33.5 (#50), GPT-5.5: 50.7 (#6)
| Benchmark | Claude Haiku 4.5 | GPT-5.5 |
|---|---|---|
| Terminal-Bench | 35.5% | 84.7% |
| DeepResearch Bench | 45.5% | 54% |
| ExploitBench | 13.7% | 47.4% |
| Vending-Bench 2 | 458.89 | 7,524 |
| APEX-Agents | — | 55.1% |
| Berkeley Function Calling Leaderboard | 68.7% | — |
| OSWorld 2.0 | — | 13% |
| Remote Labor Index | — | 6.3% |
| τ²-bench Banking | — | 44.6% |
| PostTrainBench | — | 27.2% |
| BALROG | 31.2% | — |
| GBAEval | — | 53.2% |
| GDP.pdf | — | 26% |
| LMArena Search | — | 1242 |
Reasoning GPT-5.5 leads
Claude Haiku 4.5: 15.1 (#310), GPT-5.5: 72.7 (#8)
| Benchmark | Claude Haiku 4.5 | GPT-5.5 |
|---|---|---|
| ARC-AGI-2 | 4% | 85% |
| NYT Connections (extended) | 14.3% | 96.2% |
| ARC-AGI-1 | 47.7% | 95% |
| CritPt | 0% | 27.1% |
| Chess Puzzles | 8% | 54% |
| LMArena Hard Prompts | 1420 | 1489 |
| DTBench | 73.6% | 96% |
| LMCA | 30.9% | 54.3% |
| Epoch Capabilities Index | 142.42 | 159.25 |
| ForecastBench | 61.4 | 60.6 |
| SimpleBench | — | 69% |
| Kagi LLM Benchmark | — | 88.8% |
| EBR-Bench | — | 34.3% |
| Mystery Game Puzzles | — | 56% |
| Surface Evolver Bench | — | 88.1% |
| Bench to the Future 3 | — | 0.14 |
Math GPT-5.5 leads
Claude Haiku 4.5: 43.0 (#69), GPT-5.5: 81.5 (#9)
| Benchmark | Claude Haiku 4.5 | GPT-5.5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.7% | 100% |
| LMArena Math | 1395 | 1486 |
| FrontierMath (Feb 2025 set) | 5.9% | 51.7% |
| FrontierMath Tier 4 (v1) | 2.1% | 35.4% |
| FrontierMath (Tiers 1-3) | — | 85.3% |
| FrontierMath Tier 4 | — | 72.5% |
| MathArena Final-Answer Competitions | — | 94.3% |
| ProofBench | — | 50% |
| Omni-MATH | 56.1% | — |
| MATH Level 5 | 96.4% | — |
| FrontierMath Erdős | — | 0% |
Knowledge GPT-5.5 leads
Claude Haiku 4.5: 37.6 (#146), GPT-5.5: 64.4 (#14)
| Benchmark | Claude Haiku 4.5 | GPT-5.5 |
|---|---|---|
| GPQA Diamond | 71.2% | 94% |
| SimpleQA Verified | 13.2% | 63% |
| Vectara Hallucination Rate | 9.8% | 9.3% |
| LMArena Expert | 1443 | 1508 |
| MMLU-Pro | 77.7% | — |
| GPQA (HELM) | 60.5% | — |
Multimodal GPT-5.5 leads
Claude Haiku 4.5: 27.0 (#111), GPT-5.5: 47.1 (#11)
| Benchmark | Claude Haiku 4.5 | GPT-5.5 |
|---|---|---|
| Blueprint-Bench 2 | 0% | 36.2% |
| LMArena Document | 1420 | 1486 |
| LMArena Vision | — | 1297 |
| Furniture Assembly | — | 44.2% |
Multilingual GPT-5.5 leads
Claude Haiku 4.5: 50.1 (#124), GPT-5.5: 56.5 (#19)
| Benchmark | Claude Haiku 4.5 | GPT-5.5 |
|---|---|---|
| LMArena Non-English | 1376 | 1467 |
| LMArena Chinese | 1415 | 1535 |
| LMArena French | 1408 | 1486 |
| LMArena German | 1377 | 1478 |
| LMArena Japanese | 1339 | 1498 |
| LMArena Korean | 1346 | 1461 |
| LMArena Russian | 1380 | 1473 |
| LMArena Spanish | 1420 | 1469 |
Instruction Following GPT-5.5 leads
Claude Haiku 4.5: 71.6 (#144), GPT-5.5: 77.7 (#18)
| Benchmark | Claude Haiku 4.5 | GPT-5.5 |
|---|---|---|
| LMArena Instruction Following | 1414 | 1479 |
| IFEval | 80.1% | — |
Long Context GPT-5.5 leads
Claude Haiku 4.5: 43.6 (#86), GPT-5.5: 48.3 (#12)
| Benchmark | Claude Haiku 4.5 | GPT-5.5 |
|---|---|---|
| LMArena Longer Query | 1427 | 1484 |
| CL-bench Life | — | 22.2% |
Writing & Preference GPT-5.5 leads
Claude Haiku 4.5: 58.1 (#119), GPT-5.5: 72.8 (#13)
| Benchmark | Claude Haiku 4.5 | GPT-5.5 |
|---|---|---|
| LMArena Text | 1396 | 1471 |
| LMArena Creative Writing | 1371 | 1455 |
| EQ-Bench 4 | 1064 | 1315 |
| LMArena Multi-Turn | 1409 | 1477 |
| EQ-Bench Creative Writing | — | 1844 |
| WildBench | 83.9% | — |
Frequently asked questions
Is Claude Haiku 4.5 better than GPT-5.5?
GPT-5.5 is the stronger model overall, scoring 63.4 to 39.3 on the Noometry Index. Claude Haiku 4.5 costs 5.6× less per token, which makes it the better buy when GPT-5.5's lead doesn't matter for your workload.
Which is cheaper, Claude Haiku 4.5 or GPT-5.5?
Claude Haiku 4.5 is cheaper. It lists at $1 per million input tokens and $5 per million output tokens; GPT-5.5 lists at $5 and $30.
Is Claude Haiku 4.5 or GPT-5.5 better for coding?
GPT-5.5 scores higher on coding benchmarks: 58.3 versus 43.9 in the Noometry coding category.
Which has the bigger context window?
GPT-5.5 does, with 1.05M tokens against 200K.
How many benchmarks do Claude Haiku 4.5 and GPT-5.5 share?
43 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and GPT-5.5 has 71.