Model comparison
GPT-4.1 mini vs o3-pro
o3-pro is the stronger model overall, scoring 42.9 to 33.6 on the Noometry Index. GPT-4.1 mini costs 50× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Last verified . 9 shared benchmarks.
Summary
- They share 9 benchmarks with published results for both. GPT-4.1 mini scores higher in 1 category and o3-pro in 4 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 31.8.
- The biggest single-benchmark swing is ARC-AGI-1: 3.5% for GPT-4.1 mini and 59.3% for o3-pro.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $20 / $80 for o3-pro.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 200K.
Side by side
| GPT-4.1 mini | o3-pro | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 33.6 | 42.9 |
| Released | 2025-04-14 | 2025-06-10 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 200K |
| Max output | 33K | 100K |
| Input $ / M tokens | $0.40 | $20 |
| Output $ / M tokens | $1.60 | $80 |
| Results tracked | 47 | 12 |
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Category by category
Coding o3-pro leads
GPT-4.1 mini: 30.6 (#293), o3-pro: 55.5 (#24)
| Benchmark | GPT-4.1 mini | o3-pro |
|---|---|---|
| Aider Polyglot | 32.4% | 84.9% |
| WeirdML | 37.6% | 58.2% |
| SWE-bench Verified (bash only) | 23.9% | — |
| SciCode | 40.4% | — |
| BigCodeBench Instruct | 48.9% | — |
| LMArena Coding | 1367 | — |
| CadEval | 16% | — |
Agentic & Tool Use Not comparable
GPT-4.1 mini: 33.3 (#55), o3-pro: —
| Benchmark | GPT-4.1 mini | o3-pro |
|---|---|---|
| Berkeley Function Calling Leaderboard | 50.5% | — |
Reasoning o3-pro leads
GPT-4.1 mini: 10.8 (#340), o3-pro: 23.8 (#171)
| Benchmark | GPT-4.1 mini | o3-pro |
|---|---|---|
| ARC-AGI-2 | 0% | 4.9% |
| Kagi LLM Benchmark | 48.6% | 72.1% |
| ARC-AGI-1 | 3.5% | 59.3% |
| DTBench | 68.8% | 86.9% |
| LMCA | 21.1% | 38.5% |
| Epoch Capabilities Index | 135.01 | 147.42 |
| CritPt | 0% | — |
| Chess Puzzles | 7% | — |
| LMArena Hard Prompts | 1349 | — |
| Mystery Game Puzzles | 7% | — |
Math Not comparable
GPT-4.1 mini: 24.1 (#270), o3-pro: —
| Benchmark | GPT-4.1 mini | o3-pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6.7% | — |
| OTIS Mock AIME 2024-2025 | 44.7% | — |
| Omni-MATH | 49.1% | — |
| LMArena Math | 1343 | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
Knowledge GPT-4.1 mini leads
GPT-4.1 mini: 34.7 (#194), o3-pro: 29.5 (#238)
| Benchmark | GPT-4.1 mini | o3-pro |
|---|---|---|
| GPQA Diamond | 65.8% | — |
| SimpleQA Verified | 12.7% | — |
| MMLU-Pro | 78.3% | — |
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 23.3% |
| GPQA (HELM) | 61.4% | — |
| LMArena Expert | 1338 | — |
Multimodal Not comparable
GPT-4.1 mini: 35.8 (#82), o3-pro: —
| Benchmark | GPT-4.1 mini | o3-pro |
|---|---|---|
| LMArena Vision | 1181 | — |
Multilingual Not comparable
GPT-4.1 mini: 45.7 (#166), o3-pro: —
| Benchmark | GPT-4.1 mini | o3-pro |
|---|---|---|
| LMArena Non-English | 1318 | — |
| LMArena Chinese | 1329 | — |
| LMArena French | 1358 | — |
| LMArena German | 1351 | — |
| LMArena Japanese | 1290 | — |
| LMArena Korean | 1298 | — |
| LMArena Russian | 1324 | — |
| LMArena Spanish | 1319 | — |
Instruction Following Not comparable
GPT-4.1 mini: 73.7 (#118), o3-pro: —
| Benchmark | GPT-4.1 mini | o3-pro |
|---|---|---|
| IFEval | 90.4% | — |
| LMArena Instruction Following | 1333 | — |
Long Context o3-pro leads
GPT-4.1 mini: 31.8 (#275), o3-pro: 72.2 (#1)
| Benchmark | GPT-4.1 mini | o3-pro |
|---|---|---|
| Fiction.LiveBench | 44.4% | 97.2% |
| LMArena Longer Query | 1344 | — |
Writing & Preference o3-pro leads
GPT-4.1 mini: 48.6 (#199), o3-pro: 57.1 (#133)
| Benchmark | GPT-4.1 mini | o3-pro |
|---|---|---|
| LMArena Text | 1340 | — |
| LMArena Creative Writing | 1300 | — |
| Short-Story Creative Writing | — | 84.4% |
| EQ-Bench Creative Writing | 1147 | — |
| WildBench | 83.8% | — |
| LMArena Multi-Turn | 1354 | — |
Frequently asked questions
Is GPT-4.1 mini better than o3-pro?
o3-pro is the stronger model overall, scoring 42.9 to 33.6 on the Noometry Index. GPT-4.1 mini costs 50× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 mini or o3-pro?
GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; o3-pro lists at $20 and $80.
Is GPT-4.1 mini or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 30.6 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 mini does, with 1.05M tokens against 200K.
How many benchmarks do GPT-4.1 mini and o3-pro share?
9 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and o3-pro has 12.