Model comparison
GPT-5 Mini vs o3-pro
o3-pro is the stronger model overall, scoring 42.9 to 41.8 on the Noometry Index. GPT-5 Mini costs 51× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Last verified . 11 shared benchmarks.
Summary
- They share 11 benchmarks with published results for both. GPT-5 Mini scores higher in 2 categories and o3-pro in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 41.9.
- The biggest single-benchmark swing is Fiction.LiveBench: 69.4% for GPT-5 Mini and 97.2% for o3-pro.
- GPT-5 Mini is cheaper at $0.25 / $2 per million input/output tokens, against $20 / $80 for o3-pro.
- GPT-5 Mini accepts more context: 400K tokens versus 200K.
Side by side
| GPT-5 Mini | o3-pro | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 41.8 | 42.9 |
| Released | 2025-08-07 | 2025-06-10 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 200K |
| Max output | 128K | 100K |
| Input $ / M tokens | $0.25 | $20 |
| Output $ / M tokens | $2 | $80 |
| Results tracked | 60 | 12 |
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Category by category
Coding o3-pro leads
GPT-5 Mini: 40.1 (#146), o3-pro: 55.5 (#24)
| Benchmark | GPT-5 Mini | o3-pro |
|---|---|---|
| WeirdML | 52.7% | 58.2% |
| SWE-bench Verified | 64.7% | — |
| SWE-bench Verified (bash only) | 59.8% | — |
| Aider Polyglot | — | 84.9% |
| SWE-bench Multilingual | 39.7% | — |
| SciCode | 39.2% | — |
| LMArena Coding | 1406 | — |
| ALE-Bench | 799.77 | — |
| AlgoTune | 1.38 | — |
Agentic & Tool Use Not comparable
GPT-5 Mini: 31.1 (#70), o3-pro: —
| Benchmark | GPT-5 Mini | o3-pro |
|---|---|---|
| Terminal-Bench | 34.8% | — |
| Berkeley Function Calling Leaderboard | 55.5% | — |
| Vending-Bench 2 | -31.18 | — |
Reasoning Too close to call
GPT-5 Mini: 23.9 (#168), o3-pro: 23.8 (#171)
| Benchmark | GPT-5 Mini | o3-pro |
|---|---|---|
| ARC-AGI-2 | 4.4% | 4.9% |
| Kagi LLM Benchmark | 70.3% | 72.1% |
| ARC-AGI-1 | 54.3% | 59.3% |
| DTBench | 80.5% | 86.9% |
| LMCA | 34.2% | 38.5% |
| Epoch Capabilities Index | 145.52 | 147.42 |
| CritPt | 0% | — |
| Chess Puzzles | 30% | — |
| EnigmaEval | 8.2% | — |
| LMArena Hard Prompts | 1380 | — |
| Mystery Game Puzzles | 10% | — |
| ForecastBench | 61 | — |
Math Not comparable
GPT-5 Mini: 46.7 (#69), o3-pro: —
| Benchmark | GPT-5 Mini | o3-pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | 46.7% | — |
| FrontierMath Tier 4 | 12.2% | — |
| OTIS Mock AIME 2024-2025 | 86.7% | — |
| ProofBench | 9% | — |
| Omni-MATH | 72.2% | — |
| LMArena Math | 1378 | — |
| MATH Level 5 | 97.8% | — |
| FrontierMath (Feb 2025 set) | 27.2% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |
Knowledge GPT-5 Mini leads
GPT-5 Mini: 45.6 (#86), o3-pro: 29.5 (#238)
| Benchmark | GPT-5 Mini | o3-pro |
|---|---|---|
| Confabulations | 13.3% | 14.2% |
| Vectara Hallucination Rate | 12.9% | 23.3% |
| GPQA Diamond | 75% | — |
| Humanity's Last Exam | 19.4% | — |
| SimpleQA Verified | 21.6% | — |
| MMLU-Pro | 83.5% | — |
| GPQA (HELM) | 75.6% | — |
| LMArena Expert | 1379 | — |
Multimodal Not comparable
GPT-5 Mini: 35.6 (#85), o3-pro: —
| Benchmark | GPT-5 Mini | o3-pro |
|---|---|---|
| LMArena Vision | 1202 | — |
| VPCT | 40.2% | — |
Multilingual Not comparable
GPT-5 Mini: 48.9 (#137), o3-pro: —
| Benchmark | GPT-5 Mini | o3-pro |
|---|---|---|
| LMArena Non-English | 1363 | — |
| LMArena Chinese | 1385 | — |
| LMArena French | 1386 | — |
| LMArena German | 1366 | — |
| LMArena Japanese | 1341 | — |
| LMArena Korean | 1308 | — |
| LMArena Russian | 1362 | — |
| LMArena Spanish | 1355 | — |
Instruction Following Not comparable
GPT-5 Mini: 76.2 (#46), o3-pro: —
| Benchmark | GPT-5 Mini | o3-pro |
|---|---|---|
| IFEval | 92.7% | — |
| LMArena Instruction Following | 1357 | — |
Long Context o3-pro leads
GPT-5 Mini: 41.9 (#132), o3-pro: 72.2 (#1)
| Benchmark | GPT-5 Mini | o3-pro |
|---|---|---|
| Fiction.LiveBench | 69.4% | 97.2% |
| LMArena Longer Query | 1355 | — |
Writing & Preference o3-pro leads
GPT-5 Mini: 55.2 (#148), o3-pro: 57.1 (#133)
| Benchmark | GPT-5 Mini | o3-pro |
|---|---|---|
| Short-Story Creative Writing | 83.1% | 84.4% |
| LMArena Text | 1373 | — |
| LMArena Creative Writing | 1325 | — |
| EQ-Bench Creative Writing | 1313 | — |
| WildBench | 85.5% | — |
| LMArena Multi-Turn | 1363 | — |
Frequently asked questions
Is GPT-5 Mini better than o3-pro?
o3-pro is the stronger model overall, scoring 42.9 to 41.8 on the Noometry Index. GPT-5 Mini costs 51× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5 Mini or o3-pro?
GPT-5 Mini is cheaper. It lists at $0.25 per million input tokens and $2 per million output tokens; o3-pro lists at $20 and $80.
Is GPT-5 Mini or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 40.1 in the Noometry coding category.
Which has the bigger context window?
GPT-5 Mini does, with 400K tokens against 200K.
How many benchmarks do GPT-5 Mini and o3-pro share?
11 benchmarks have published results for both models. GPT-5 Mini has 60 scored results on Noometry and o3-pro has 12.