Model comparison
GPT-4.1 mini vs GPT-5
GPT-5 is the stronger model overall, scoring 50.9 to 33.6 on the Noometry Index. GPT-4.1 mini costs 4.9× less per token, which makes it the better buy when GPT-5's lead doesn't matter for your workload.
Last verified . 44 shared benchmarks.
Summary
- They share 44 benchmarks with published results for both. GPT-4.1 mini scores higher in 1 category and GPT-5 in 9 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where GPT-5 leads 69.5 to 31.8.
- The biggest single-benchmark swing is ARC-AGI-1: 3.5% for GPT-4.1 mini and 65.7% for GPT-5.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $1.25 / $10 for GPT-5.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 400K.
Side by side
| GPT-4.1 mini | GPT-5 | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 33.6 | 50.9 |
| Released | 2025-04-14 | 2025-08-07 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 400K |
| Max output | 33K | 128K |
| Input $ / M tokens | $0.40 | $1.25 |
| Output $ / M tokens | $1.60 | $10 |
| Results tracked | 47 | 69 |
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Category by category
Coding GPT-5 leads
GPT-4.1 mini: 30.6 (#293), GPT-5: 50.3 (#47)
| Benchmark | GPT-4.1 mini | GPT-5 |
|---|---|---|
| SWE-bench Verified (bash only) | 23.9% | 65% |
| Aider Polyglot | 32.4% | 88% |
| SciCode | 40.4% | 42.9% |
| WeirdML | 37.6% | 60.7% |
| LMArena Coding | 1367 | 1436 |
| SWE-bench Verified | — | 73.6% |
| LMArena WebDev | — | 1418 |
| GSO | — | 6.9% |
| BigCodeBench Instruct | 48.9% | — |
| CadEval | 16% | — |
| ALE-Bench | — | 1,162 |
| AlgoTune | — | 1.67 |
Agentic & Tool Use Too close to call
GPT-4.1 mini: 33.3 (#55), GPT-5: 33.1 (#56)
| Benchmark | GPT-4.1 mini | GPT-5 |
|---|---|---|
| Terminal-Bench | — | 49.6% |
| Berkeley Function Calling Leaderboard | 50.5% | — |
| GDPval | — | 34.8% |
| Remote Labor Index | — | 1.7% |
| DeepResearch Bench | — | 49.6% |
| BALROG | — | 32.8% |
| LMArena Search | — | 1133 |
| METR Time Horizons | — | 69.6% |
Reasoning GPT-5 leads
GPT-4.1 mini: 10.8 (#340), GPT-5: 38.3 (#64)
| Benchmark | GPT-4.1 mini | GPT-5 |
|---|---|---|
| ARC-AGI-2 | 0% | 9.9% |
| Kagi LLM Benchmark | 48.6% | 72.7% |
| ARC-AGI-1 | 3.5% | 65.7% |
| CritPt | 0% | 12.6% |
| Chess Puzzles | 7% | 37% |
| LMArena Hard Prompts | 1349 | 1416 |
| Mystery Game Puzzles | 7% | 23% |
| DTBench | 68.8% | 90.7% |
| LMCA | 21.1% | 40% |
| Epoch Capabilities Index | 135.01 | 150 |
| SimpleBench | — | 56.7% |
| EnigmaEval | — | 10.5% |
| EBR-Bench | — | 12.7% |
| ForecastBench | — | 61.4 |
Math GPT-5 leads
GPT-4.1 mini: 24.1 (#270), GPT-5: 55.0 (#44)
| Benchmark | GPT-4.1 mini | GPT-5 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6.7% | 55.4% |
| OTIS Mock AIME 2024-2025 | 44.7% | 91.4% |
| Omni-MATH | 49.1% | 64.7% |
| LMArena Math | 1343 | 1407 |
| MATH Level 5 | 87.3% | 98.1% |
| FrontierMath (Feb 2025 set) | 4.5% | 32.4% |
| FrontierMath Tier 4 | — | 22% |
| ProofBench | — | 18% |
| FrontierMath Tier 4 (v1) | — | 12.5% |
Knowledge GPT-5 leads
GPT-4.1 mini: 34.7 (#194), GPT-5: 56.6 (#43)
| Benchmark | GPT-4.1 mini | GPT-5 |
|---|---|---|
| GPQA Diamond | 65.8% | 86.2% |
| SimpleQA Verified | 12.7% | 50.1% |
| MMLU-Pro | 78.3% | 86.3% |
| GPQA (HELM) | 61.4% | 79.2% |
| LMArena Expert | 1338 | 1419 |
| Humanity's Last Exam | — | 25.3% |
| Confabulations | — | 10.3% |
| Vectara Hallucination Rate | — | 14.7% |
Multimodal GPT-5 leads
GPT-4.1 mini: 35.8 (#82), GPT-5: 46.8 (#13)
| Benchmark | GPT-4.1 mini | GPT-5 |
|---|---|---|
| LMArena Vision | 1181 | 1232 |
| GeoBench | — | 81% |
| VPCT | — | 66% |
Multilingual GPT-5 leads
GPT-4.1 mini: 45.7 (#166), GPT-5: 51.4 (#110)
| Benchmark | GPT-4.1 mini | GPT-5 |
|---|---|---|
| LMArena Non-English | 1318 | 1397 |
| LMArena Chinese | 1329 | 1422 |
| LMArena French | 1358 | 1410 |
| LMArena German | 1351 | 1416 |
| LMArena Japanese | 1290 | 1409 |
| LMArena Korean | 1298 | 1360 |
| LMArena Russian | 1324 | 1406 |
| LMArena Spanish | 1319 | 1399 |
Instruction Following Too close to call
GPT-4.1 mini: 73.7 (#118), GPT-5: 73.8 (#113)
| Benchmark | GPT-4.1 mini | GPT-5 |
|---|---|---|
| IFEval | 90.4% | 87.5% |
| LMArena Instruction Following | 1333 | 1388 |
Long Context GPT-5 leads
GPT-4.1 mini: 31.8 (#275), GPT-5: 69.5 (#2)
| Benchmark | GPT-4.1 mini | GPT-5 |
|---|---|---|
| Fiction.LiveBench | 44.4% | 97.2% |
| LMArena Longer Query | 1344 | 1399 |
Writing & Preference GPT-5 leads
GPT-4.1 mini: 48.6 (#199), GPT-5: 63.4 (#65)
| Benchmark | GPT-4.1 mini | GPT-5 |
|---|---|---|
| LMArena Text | 1340 | 1406 |
| LMArena Creative Writing | 1300 | 1365 |
| EQ-Bench Creative Writing | 1147 | 1627 |
| WildBench | 83.8% | 85.7% |
| LMArena Multi-Turn | 1354 | 1426 |
| Short-Story Creative Writing | — | 86% |
Frequently asked questions
Is GPT-4.1 mini better than GPT-5?
GPT-5 is the stronger model overall, scoring 50.9 to 33.6 on the Noometry Index. GPT-4.1 mini costs 4.9× less per token, which makes it the better buy when GPT-5's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 mini or GPT-5?
GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; GPT-5 lists at $1.25 and $10.
Is GPT-4.1 mini or GPT-5 better for coding?
GPT-5 scores higher on coding benchmarks: 50.3 versus 30.6 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 mini does, with 1.05M tokens against 400K.
How many benchmarks do GPT-4.1 mini and GPT-5 share?
44 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and GPT-5 has 69.