Model comparison
Claude Haiku 4.5 vs GPT-4
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 29.1 on the Noometry Index.
Last verified . 26 shared benchmarks.
Summary
- They share 26 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 7 categories and GPT-4 in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Haiku 4.5 leads 44.9 to 10.8.
- The biggest single-benchmark swing is MATH Level 5: 96.4% for Claude Haiku 4.5 and 23% for GPT-4.
- Claude Haiku 4.5 is cheaper at $1 / $5 per million input/output tokens, against $30 / $60 for GPT-4.
- Claude Haiku 4.5 accepts more context: 200K tokens versus 8K.
Side by side
| Claude Haiku 4.5 | GPT-4 | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 39.5 | 29.1 |
| Released | 2025-10-15 | 2023-03-14 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 8K |
| Max output | 64K | 8K |
| Input $ / M tokens | $1 | $30 |
| Output $ / M tokens | $5 | $60 |
| Results tracked | 53 | 38 |
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Category by category
Coding Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.0 (#78), GPT-4: 31.6 (#283)
| Benchmark | Claude Haiku 4.5 | GPT-4 |
|---|---|---|
| WeirdML | 45.4% | 12.4% |
| LMArena Coding | 1453 | 1254 |
| SWE-bench Verified (bash only) | 66.6% | — |
| LMArena WebDev | 1330 | — |
| SWE-bench Multilingual | 64.7% | — |
| SciCode | 43.3% | — |
| BigCodeBench Instruct | — | 46% |
| BigCodeBench Complete | — | 57.2% |
| ALE-Bench | 653.48 | — |
| HumanEval+ | — | 79.3% |
Agentic & Tool Use Not comparable
Claude Haiku 4.5: 33.6 (#52), GPT-4: —
| Benchmark | Claude Haiku 4.5 | GPT-4 |
|---|---|---|
| Terminal-Bench | 35.5% | — |
| Berkeley Function Calling Leaderboard | 68.7% | — |
| DeepResearch Bench | 45.5% | — |
| BALROG | 31.2% | — |
| ExploitBench | 13.7% | — |
| METR Time Horizons | — | 36.1% |
| Vending-Bench 2 | 458.89 | — |
Reasoning GPT-4 leads
Claude Haiku 4.5: 15.1 (#320), GPT-4: 17.8 (#289)
| Benchmark | Claude Haiku 4.5 | GPT-4 |
|---|---|---|
| Chess Puzzles | 8% | 4% |
| LMArena Hard Prompts | 1420 | 1241 |
| DTBench | 73.6% | 62.7% |
| LMCA | 30.9% | 17.1% |
| Epoch Capabilities Index | 142.41 | 125.89 |
| ForecastBench | 61.4 | 57.8 |
| ARC-AGI-2 | 4% | — |
| NYT Connections (extended) | 14.3% | — |
| ARC-AGI-1 | 47.7% | — |
| CritPt | 0% | — |
| Mystery Game Puzzles | — | 12% |
| BIG-Bench Hard | — | 75.1% |
| HellaSwag | — | 95.3% |
| WinoGrande | — | 87.5% |
Math Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.9 (#78), GPT-4: 10.8 (#309)
| Benchmark | Claude Haiku 4.5 | GPT-4 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.7% | 1.1% |
| LMArena Math | 1396 | 1269 |
| MATH Level 5 | 96.4% | 23% |
| Omni-MATH | 56.1% | — |
| FrontierMath (Feb 2025 set) | 5.9% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
| GSM8K | — | 92% |
Knowledge Claude Haiku 4.5 leads
Claude Haiku 4.5: 37.7 (#153), GPT-4: 18.4 (#282)
| Benchmark | Claude Haiku 4.5 | GPT-4 |
|---|---|---|
| GPQA Diamond | 71.2% | 35.7% |
| LMArena Expert | 1442 | 1211 |
| SimpleQA Verified | 13.2% | — |
| MMLU-Pro | 77.7% | — |
| Vectara Hallucination Rate | 9.8% | — |
| GPQA (HELM) | 60.5% | — |
| MMLU | — | 86.4% |
| TriviaQA | — | 84.8% |
Multimodal Not comparable
Claude Haiku 4.5: 26.8 (#118), GPT-4: —
| Benchmark | Claude Haiku 4.5 | GPT-4 |
|---|---|---|
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1420 | — |
Multilingual Claude Haiku 4.5 leads
Claude Haiku 4.5: 49.9 (#129), GPT-4: 40.6 (#215)
| Benchmark | Claude Haiku 4.5 | GPT-4 |
|---|---|---|
| LMArena Non-English | 1377 | 1246 |
| LMArena Chinese | 1417 | 1242 |
| LMArena French | 1408 | 1283 |
| LMArena German | 1375 | 1251 |
| LMArena Japanese | 1339 | 1209 |
| LMArena Korean | 1347 | 1184 |
| LMArena Russian | 1381 | 1251 |
| LMArena Spanish | 1420 | 1261 |
Instruction Following Claude Haiku 4.5 leads
Claude Haiku 4.5: 71.4 (#149), GPT-4: 65.3 (#222)
| Benchmark | Claude Haiku 4.5 | GPT-4 |
|---|---|---|
| LMArena Instruction Following | 1414 | 1241 |
| IFEval | 80.1% | — |
Long Context Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.6 (#92), GPT-4: 37.7 (#212)
| Benchmark | Claude Haiku 4.5 | GPT-4 |
|---|---|---|
| LMArena Longer Query | 1427 | 1244 |
Writing & Preference Claude Haiku 4.5 leads
Claude Haiku 4.5: 57.9 (#123), GPT-4: 34.9 (#268)
| Benchmark | Claude Haiku 4.5 | GPT-4 |
|---|---|---|
| LMArena Text | 1396 | 1263 |
| LMArena Creative Writing | 1372 | 1244 |
| LMArena Multi-Turn | 1409 | 1257 |
| EQ-Bench Creative Writing | — | 752 |
| WildBench | 83.9% | — |
| EQ-Bench 4 | 1064 | — |
Frequently asked questions
Is Claude Haiku 4.5 better than GPT-4?
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 29.1 on the Noometry Index.
Which is cheaper, Claude Haiku 4.5 or GPT-4?
Claude Haiku 4.5 is cheaper. It lists at $1 per million input tokens and $5 per million output tokens; GPT-4 lists at $30 and $60.
Is Claude Haiku 4.5 or GPT-4 better for coding?
Claude Haiku 4.5 scores higher on coding benchmarks: 44.0 versus 31.6 in the Noometry coding category.
Which has the bigger context window?
Claude Haiku 4.5 does, with 200K tokens against 8K.
How many benchmarks do Claude Haiku 4.5 and GPT-4 share?
26 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and GPT-4 has 38.