Model comparison
Claude Opus 4 vs GPT-3.5-turbo
Claude Opus 4 is the stronger model overall, scoring 43.1 to 23.2 on the Noometry Index. GPT-3.5-turbo costs 40× less per token, which makes it the better buy when Claude Opus 4's lead doesn't matter for your workload.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. Claude Opus 4 scores higher in 8 categories and GPT-3.5-turbo in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Claude Opus 4 leads 61.2 to 25.3.
- The biggest single-benchmark swing is MATH Level 5: 85% for Claude Opus 4 and 15.9% for GPT-3.5-turbo.
- GPT-3.5-turbo is cheaper at $0.50 / $1.50 per million input/output tokens, against $15 / $75 for Claude Opus 4.
- Claude Opus 4 accepts more context: 200K tokens versus 16K.
Side by side
| Claude Opus 4 | GPT-3.5-turbo | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 43.1 | 23.2 |
| Released | 2025-05-22 | 2023-03-01 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 16K |
| Max output | 32K | 4K |
| Input $ / M tokens | $15 | $0.50 |
| Output $ / M tokens | $75 | $1.50 |
| Results tracked | 56 | 44 |
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Category by category
Coding Claude Opus 4 leads
Claude Opus 4: 47.2 (#62), GPT-3.5-turbo: 23.9 (#331)
| Benchmark | Claude Opus 4 | GPT-3.5-turbo |
|---|---|---|
| WeirdML | 43.7% | 3.5% |
| LMArena Coding | 1442 | 1136 |
| SWE-bench Verified | 70.7% | — |
| SWE-bench Verified (bash only) | 67.6% | — |
| Aider Polyglot | 72% | — |
| GSO | 6.9% | — |
| BigCodeBench Instruct | — | 39.1% |
| BigCodeBench Complete | — | 50.6% |
| AlgoTune | 1.33 | — |
| HumanEval+ | — | 70.7% |
| MBPP+ | — | 69.7% |
Agentic & Tool Use Not comparable
Claude Opus 4: 34.8 (#42), GPT-3.5-turbo: —
| Benchmark | Claude Opus 4 | GPT-3.5-turbo |
|---|---|---|
| METR Time Horizons | 63.9% | 21.5% |
| Cybench | 38% | — |
| DeepResearch Bench | 46.8% | — |
| LMArena Search | 1127 | — |
Reasoning Claude Opus 4 leads
Claude Opus 4: 27.3 (#121), GPT-3.5-turbo: 13.8 (#332)
| Benchmark | Claude Opus 4 | GPT-3.5-turbo |
|---|---|---|
| LMArena Hard Prompts | 1399 | 1108 |
| DTBench | 81.6% | 48.5% |
| LMCA | 37.4% | 9.7% |
| Epoch Capabilities Index | 142.67 | 118.55 |
| ForecastBench | 61.1 | 50.4 |
| ARC-AGI-2 | 8.6% | — |
| SimpleBench | 58.8% | — |
| Kagi LLM Benchmark | 74.3% | — |
| ARC-AGI-1 | 35.7% | — |
| CritPt | 0.3% | — |
| Chess Puzzles | — | 0% |
| EnigmaEval | 5.6% | — |
| Mystery Game Puzzles | — | 3% |
| Adversarial NLI | — | 58.1% |
| BIG-Bench Hard | — | 61.6% |
| CommonsenseQA 2.0 | — | 57% |
| WinoGrande | — | 81.6% |
Math Claude Opus 4 leads
Claude Opus 4: 42.0 (#86), GPT-3.5-turbo: 6.3 (#327)
| Benchmark | Claude Opus 4 | GPT-3.5-turbo |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 64.4% | 2.2% |
| LMArena Math | 1390 | 1142 |
| MATH Level 5 | 85% | 15.9% |
| FrontierMath (Tiers 1-3) | — | 0% |
| Omni-MATH | 61.6% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
| GSM8K | — | 57.8% |
Knowledge Claude Opus 4 leads
Claude Opus 4: 44.0 (#88), GPT-3.5-turbo: 10.0 (#303)
| Benchmark | Claude Opus 4 | GPT-3.5-turbo |
|---|---|---|
| GPQA Diamond | 76.3% | 28% |
| LMArena Expert | 1386 | 1070 |
| Humanity's Last Exam | 10.7% | — |
| MMLU-Pro | 87.5% | — |
| Confabulations | 15.9% | — |
| Vectara Hallucination Rate | 12% | — |
| GPQA (HELM) | 70.8% | — |
| ARC (AI2) Challenge | — | 87.4% |
| BoolQ | — | 87% |
| MMLU | — | 71.4% |
| OpenBookQA | — | 86% |
| TriviaQA | — | 85.8% |
Multimodal Not comparable
Claude Opus 4: 31.5 (#106), GPT-3.5-turbo: —
| Benchmark | Claude Opus 4 | GPT-3.5-turbo |
|---|---|---|
| LMArena Vision | 1192 | — |
| GeoBench | 49% | — |
| VPCT | 38% | — |
Multilingual Claude Opus 4 leads
Claude Opus 4: 48.8 (#138), GPT-3.5-turbo: 31.5 (#258)
| Benchmark | Claude Opus 4 | GPT-3.5-turbo |
|---|---|---|
| LMArena Non-English | 1362 | 1108 |
| LMArena Chinese | 1386 | 1075 |
| LMArena French | 1372 | 1118 |
| LMArena German | 1391 | 1090 |
| LMArena Japanese | 1331 | 1043 |
| LMArena Korean | 1321 | 1019 |
| LMArena Russian | 1392 | 1123 |
| LMArena Spanish | 1389 | 1121 |
Instruction Following Claude Opus 4 leads
Claude Opus 4: 77.1 (#28), GPT-3.5-turbo: 57.9 (#262)
| Benchmark | Claude Opus 4 | GPT-3.5-turbo |
|---|---|---|
| LMArena Instruction Following | 1406 | 1119 |
| IFEval | 91.8% | — |
Long Context Claude Opus 4 leads
Claude Opus 4: 39.6 (#172), GPT-3.5-turbo: 34.0 (#254)
| Benchmark | Claude Opus 4 | GPT-3.5-turbo |
|---|---|---|
| LMArena Longer Query | 1422 | 1121 |
| Fiction.LiveBench | 61.1% | — |
Writing & Preference Claude Opus 4 leads
Claude Opus 4: 61.2 (#89), GPT-3.5-turbo: 25.3 (#305)
| Benchmark | Claude Opus 4 | GPT-3.5-turbo |
|---|---|---|
| LMArena Text | 1377 | 1125 |
| LMArena Creative Writing | 1387 | 1092 |
| EQ-Bench Creative Writing | 1580 | 451 |
| LMArena Multi-Turn | 1396 | 1117 |
| Short-Story Creative Writing | 83.6% | — |
| WildBench | 85.2% | — |
Frequently asked questions
Is Claude Opus 4 better than GPT-3.5-turbo?
Claude Opus 4 is the stronger model overall, scoring 43.1 to 23.2 on the Noometry Index. GPT-3.5-turbo costs 40× 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-3.5-turbo?
GPT-3.5-turbo is cheaper. It lists at $0.50 per million input tokens and $1.50 per million output tokens; Claude Opus 4 lists at $15 and $75.
Is Claude Opus 4 or GPT-3.5-turbo better for coding?
Claude Opus 4 scores higher on coding benchmarks: 47.2 versus 23.9 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 4 does, with 200K tokens against 16K.
How many benchmarks do Claude Opus 4 and GPT-3.5-turbo share?
27 benchmarks have published results for both models. Claude Opus 4 has 56 scored results on Noometry and GPT-3.5-turbo has 44.