Model comparison
Claude Opus 4 vs GPT-4 Turbo
Claude Opus 4 is the stronger model overall, scoring 43.1 to 30.5 on the Noometry Index. GPT-4 Turbo costs 2.0× less per token, which makes it the better buy when Claude Opus 4's lead doesn't matter for your workload.
Last verified . 29 shared benchmarks.
Summary
- They share 29 benchmarks with published results for both. Claude Opus 4 scores higher in 9 categories and GPT-4 Turbo in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Opus 4 leads 42.0 to 9.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 64.4% for Claude Opus 4 and 6.7% for GPT-4 Turbo.
- GPT-4 Turbo is cheaper at $10 / $30 per million input/output tokens, against $15 / $75 for Claude Opus 4.
- Claude Opus 4 accepts more context: 200K tokens versus 128K.
Side by side
| Claude Opus 4 | GPT-4 Turbo | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 43.1 | 30.5 |
| Released | 2025-05-22 | 2023-11-06 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 128K |
| Max output | 32K | 4K |
| Input $ / M tokens | $15 | $10 |
| Output $ / M tokens | $75 | $30 |
| Results tracked | 56 | 36 |
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Category by category
Coding Claude Opus 4 leads
Claude Opus 4: 47.2 (#62), GPT-4 Turbo: 33.8 (#249)
| Benchmark | Claude Opus 4 | GPT-4 Turbo |
|---|---|---|
| WeirdML | 43.7% | 18% |
| LMArena Coding | 1442 | 1268 |
| SWE-bench Verified | 70.7% | — |
| SWE-bench Verified (bash only) | 67.6% | — |
| Aider Polyglot | 72% | — |
| GSO | 6.9% | — |
| BigCodeBench Instruct | — | 48.2% |
| BigCodeBench Complete | — | 58.2% |
| AlgoTune | 1.33 | — |
| HumanEval+ | — | 86.6% |
| MBPP+ | — | 73.3% |
Agentic & Tool Use Not comparable
Claude Opus 4: 34.8 (#42), GPT-4 Turbo: —
| Benchmark | Claude Opus 4 | GPT-4 Turbo |
|---|---|---|
| METR Time Horizons | 63.9% | 36.7% |
| Cybench | 38% | — |
| DeepResearch Bench | 46.8% | — |
| LMArena Search | 1127 | — |
Reasoning Claude Opus 4 leads
Claude Opus 4: 27.3 (#121), GPT-4 Turbo: 15.3 (#317)
| Benchmark | Claude Opus 4 | GPT-4 Turbo |
|---|---|---|
| SimpleBench | 58.8% | 25.1% |
| LMArena Hard Prompts | 1399 | 1251 |
| DTBench | 81.6% | 61.6% |
| LMCA | 37.4% | 9.8% |
| Epoch Capabilities Index | 142.67 | 127.25 |
| ForecastBench | 61.1 | 59.4 |
| ARC-AGI-2 | 8.6% | — |
| Kagi LLM Benchmark | 74.3% | — |
| ARC-AGI-1 | 35.7% | — |
| CritPt | 0.3% | — |
| Chess Puzzles | — | 6% |
| EnigmaEval | 5.6% | — |
Math Claude Opus 4 leads
Claude Opus 4: 42.0 (#86), GPT-4 Turbo: 9.0 (#322)
| Benchmark | Claude Opus 4 | GPT-4 Turbo |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 64.4% | 6.7% |
| LMArena Math | 1390 | 1272 |
| MATH Level 5 | 85% | 46.7% |
| FrontierMath (Tiers 1-3) | — | 0.7% |
| Omni-MATH | 61.6% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Claude Opus 4 leads
Claude Opus 4: 44.0 (#88), GPT-4 Turbo: 24.3 (#268)
| Benchmark | Claude Opus 4 | GPT-4 Turbo |
|---|---|---|
| GPQA Diamond | 76.3% | 46.6% |
| Confabulations | 15.9% | 28.4% |
| LMArena Expert | 1386 | 1223 |
| Humanity's Last Exam | 10.7% | — |
| MMLU-Pro | 87.5% | — |
| Vectara Hallucination Rate | 12% | — |
| GPQA (HELM) | 70.8% | — |
| MMLU | — | 81.3% |
Multimodal Too close to call
Claude Opus 4: 31.5 (#106), GPT-4 Turbo: 30.6 (#110)
| Benchmark | Claude Opus 4 | GPT-4 Turbo |
|---|---|---|
| LMArena Vision | 1192 | 1090 |
| GeoBench | 49% | — |
| VPCT | 38% | — |
Multilingual Claude Opus 4 leads
Claude Opus 4: 48.8 (#138), GPT-4 Turbo: 40.5 (#216)
| Benchmark | Claude Opus 4 | GPT-4 Turbo |
|---|---|---|
| LMArena Non-English | 1362 | 1245 |
| LMArena Chinese | 1386 | 1242 |
| LMArena French | 1372 | 1276 |
| LMArena German | 1391 | 1259 |
| LMArena Japanese | 1331 | 1194 |
| LMArena Korean | 1321 | 1187 |
| LMArena Russian | 1392 | 1259 |
| LMArena Spanish | 1389 | 1260 |
Instruction Following Claude Opus 4 leads
Claude Opus 4: 77.1 (#28), GPT-4 Turbo: 65.8 (#216)
| Benchmark | Claude Opus 4 | GPT-4 Turbo |
|---|---|---|
| LMArena Instruction Following | 1406 | 1249 |
| IFEval | 91.8% | — |
Long Context Claude Opus 4 leads
Claude Opus 4: 39.6 (#172), GPT-4 Turbo: 38.0 (#206)
| Benchmark | Claude Opus 4 | GPT-4 Turbo |
|---|---|---|
| LMArena Longer Query | 1422 | 1254 |
| Fiction.LiveBench | 61.1% | — |
Writing & Preference Claude Opus 4 leads
Claude Opus 4: 61.2 (#89), GPT-4 Turbo: 47.7 (#206)
| Benchmark | Claude Opus 4 | GPT-4 Turbo |
|---|---|---|
| LMArena Text | 1377 | 1272 |
| LMArena Creative Writing | 1387 | 1269 |
| LMArena Multi-Turn | 1396 | 1267 |
| Short-Story Creative Writing | 83.6% | — |
| EQ-Bench Creative Writing | 1580 | — |
| WildBench | 85.2% | — |
Frequently asked questions
Is Claude Opus 4 better than GPT-4 Turbo?
Claude Opus 4 is the stronger model overall, scoring 43.1 to 30.5 on the Noometry Index. GPT-4 Turbo costs 2.0× less per token, which makes it the better buy when Claude Opus 4's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4 or GPT-4 Turbo?
GPT-4 Turbo is cheaper. It lists at $10 per million input tokens and $30 per million output tokens; Claude Opus 4 lists at $15 and $75.
Is Claude Opus 4 or GPT-4 Turbo better for coding?
Claude Opus 4 scores higher on coding benchmarks: 47.2 versus 33.8 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 4 does, with 200K tokens against 128K.
How many benchmarks do Claude Opus 4 and GPT-4 Turbo share?
29 benchmarks have published results for both models. Claude Opus 4 has 56 scored results on Noometry and GPT-4 Turbo has 36.