Model comparison
Claude 3.5 Haiku vs GPT-6 Astra
GPT-6 Astra is the stronger model overall, scoring 70.8 to 29.2 on the Noometry Index.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. Claude 3.5 Haiku scores higher in 0 categories and GPT-6 Astra in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Astra leads 93.5 to 14.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 4.3% for Claude 3.5 Haiku and 100% for GPT-6 Astra.
Side by side
| Claude 3.5 Haiku | GPT-6 Astra | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 29.2 | 70.8 |
| Released | 2024-10-22 | 2026-09-03 |
| Weights | Proprietary | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 128K |
| Input $ / M tokens | — | $10 |
| Output $ / M tokens | — | $50 |
| Results tracked | 49 | 56 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-6 Astra leads
Claude 3.5 Haiku: 32.9 (#265), GPT-6 Astra: 73.7 (#2)
| Benchmark | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
| SciCode | 27.4% | 56.5% |
| WeirdML | 30.7% | 93.6% |
| LMArena Coding | 1286 | 1487 |
| DeepSWE | — | 74.1% |
| FrontierCode | — | 53.3% |
| Aider Polyglot | 28% | — |
| LMArena WebDev | — | 1786 |
| FrontierSWE | — | 65.5% |
| GSO | — | 79.4% |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 51.4% | — |
| MirrorCode | — | 46.7% |
| BigCodeBench Complete | 59% | — |
| CadEval | 32% | — |
| ALE-Bench | — | 2,951 |
Agentic & Tool Use GPT-6 Astra leads
Claude 3.5 Haiku: 28.0 (#95), GPT-6 Astra: 52.9 (#3)
| Benchmark | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
| BALROG | 19.3% | 68.3% |
| APEX-Agents | — | 64.7% |
| Remote Labor Index | — | 20.8% |
| GDP.pdf | — | 34.2% |
| Vending-Bench 2 | — | 15,515 |
Reasoning GPT-6 Astra leads
Claude 3.5 Haiku: 17.7 (#290), GPT-6 Astra: 85.1 (#1)
| Benchmark | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
| CritPt | 0% | 31.7% |
| LMArena Hard Prompts | 1251 | 1462 |
| DTBench | 56.7% | 97.3% |
| Epoch Capabilities Index | 127.15 | 166.45 |
| ARC-AGI-2 | — | 95% |
| NYT Connections (extended) | — | 98.1% |
| ARC-AGI-1 | — | 98.5% |
| Chess Puzzles | — | 72% |
| EBR-Bench | — | 76.2% |
| LiveBench Reasoning | 28.1% | — |
| Mystery Game Puzzles | — | 84% |
| LiveBench Data Analysis | 48.5% | — |
| LMCA | — | 64.4% |
| Bench to the Future 3 | — | 0.14 |
| LiveBench | 43.5% | — |
Math GPT-6 Astra leads
Claude 3.5 Haiku: 14.7 (#300), GPT-6 Astra: 93.5 (#2)
| Benchmark | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 4.3% | 100% |
| LMArena Math | 1244 | 1465 |
| FrontierMath (Tiers 1-3) | — | 93.7% |
| FrontierMath Tier 4 | — | 97.6% |
| ProofBench | — | 99% |
| Omni-MATH | 22.4% | — |
| LiveBench Math | 35.5% | — |
| MATH Level 5 | 46.4% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |
| FrontierMath Erdős | — | 2.9% |
Knowledge GPT-6 Astra leads
Claude 3.5 Haiku: 18.7 (#281), GPT-6 Astra: 75.3 (#1)
| Benchmark | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
| GPQA Diamond | 38.1% | 95.8% |
| LMArena Expert | 1208 | 1483 |
| Humanity's Last Exam | — | 54.8% |
| SimpleQA Verified | — | 75.6% |
| MMLU-Pro | 60.5% | — |
| Confabulations | 36.7% | — |
| Vectara Hallucination Rate | — | 8.7% |
| GPQA (HELM) | 36.3% | — |
| MMLU | 74.3% | — |
Multimodal GPT-6 Astra leads
Claude 3.5 Haiku: 26.8 (#117), GPT-6 Astra: 55.0 (#3)
| Benchmark | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
| LMArena Vision | 1092 | 1281 |
| GeoBench | 34% | — |
| Blueprint-Bench 2 | — | 49.7% |
| Furniture Assembly | — | 80% |
| LMArena Document | — | 1468 |
Multilingual GPT-6 Astra leads
Claude 3.5 Haiku: 40.0 (#218), GPT-6 Astra: 53.7 (#61)
| Benchmark | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
| LMArena Non-English | 1238 | 1430 |
| LMArena Chinese | 1229 | 1484 |
| LMArena French | 1264 | 1456 |
| LMArena German | 1237 | 1440 |
| LMArena Japanese | 1175 | 1379 |
| LMArena Korean | 1173 | 1426 |
| LMArena Russian | 1253 | 1436 |
| LMArena Spanish | 1261 | 1407 |
Instruction Following GPT-6 Astra leads
Claude 3.5 Haiku: 62.9 (#234), GPT-6 Astra: 76.3 (#44)
| Benchmark | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
| LMArena Instruction Following | 1241 | 1450 |
| LiveBench Instruction Following | 61.9% | — |
| IFEval | 79.2% | — |
Long Context GPT-6 Astra leads
Claude 3.5 Haiku: 38.3 (#200), GPT-6 Astra: 44.5 (#62)
| Benchmark | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
| LMArena Longer Query | 1261 | 1456 |
Writing & Preference GPT-6 Astra leads
Claude 3.5 Haiku: 42.7 (#234), GPT-6 Astra: 75.3 (#7)
| Benchmark | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
| LMArena Text | 1255 | 1441 |
| LMArena Creative Writing | 1233 | 1418 |
| EQ-Bench Creative Writing | 1146 | 2173 |
| LMArena Multi-Turn | 1265 | 1448 |
| Short-Story Creative Writing | 73.5% | — |
| WildBench | 76% | — |
| LiveBench Language | 35.4% | — |
Frequently asked questions
Is Claude 3.5 Haiku better than GPT-6 Astra?
GPT-6 Astra is the stronger model overall, scoring 70.8 to 29.2 on the Noometry Index.
Is Claude 3.5 Haiku or GPT-6 Astra better for coding?
GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 32.9 in the Noometry coding category.
How many benchmarks do Claude 3.5 Haiku and GPT-6 Astra share?
27 benchmarks have published results for both models. Claude 3.5 Haiku has 49 scored results on Noometry and GPT-6 Astra has 56.