Model comparison
GPT-4o mini vs GPT-5.4 mini
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 25.5 on the Noometry Index. GPT-4o mini costs 6.4× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Last verified . 31 shared benchmarks.
Summary
- They share 31 benchmarks with published results for both. GPT-4o mini scores higher in 0 categories and GPT-5.4 mini in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.4 mini leads 45.5 to 10.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 6.9% for GPT-4o mini and 88.9% for GPT-5.4 mini.
- GPT-4o mini is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.75 / $4.50 for GPT-5.4 mini.
- GPT-5.4 mini accepts more context: 400K tokens versus 128K.
Side by side
| GPT-4o mini | GPT-5.4 mini | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 25.5 | 45.0 |
| Released | 2024-07-18 | 2026-03-17 |
| Weights | Proprietary | Proprietary |
| Context window | 128K | 400K |
| Max output | 16K | 128K |
| Input $ / M tokens | $0.15 | $0.75 |
| Output $ / M tokens | $0.60 | $4.50 |
| Results tracked | 60 | 46 |
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Category by category
Coding GPT-5.4 mini leads
GPT-4o mini: 22.0 (#335), GPT-5.4 mini: 45.2 (#72)
| Benchmark | GPT-4o mini | GPT-5.4 mini |
|---|---|---|
| WeirdML | 11.8% | 60.3% |
| LMArena Coding | 1290 | 1438 |
| FrontierCode | — | 27% |
| Aider Polyglot | 3.6% | — |
| LMArena WebDev | — | 1397 |
| SciCode | — | 49.9% |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 43.1% | — |
| BigCodeBench Complete | 57.4% | — |
| ALE-Bench | — | 1,189 |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use GPT-5.4 mini leads
GPT-4o mini: 27.5 (#101), GPT-5.4 mini: 29.9 (#81)
| Benchmark | GPT-4o mini | GPT-5.4 mini |
|---|---|---|
| DeepResearch Bench | — | 36.3% |
| BALROG | 17.4% | — |
Reasoning GPT-5.4 mini leads
GPT-4o mini: 8.7 (#347), GPT-5.4 mini: 30.4 (#85)
| Benchmark | GPT-4o mini | GPT-5.4 mini |
|---|---|---|
| ARC-AGI-2 | 0% | 18.9% |
| Kagi LLM Benchmark | 28.8% | 37.9% |
| Chess Puzzles | 0% | 24% |
| LMArena Hard Prompts | 1267 | 1424 |
| Mystery Game Puzzles | 12% | 11% |
| DTBench | 54.4% | 80% |
| LMCA | 10.4% | 40.8% |
| Epoch Capabilities Index | 126.56 | 148.84 |
| SimpleBench | 10.7% | — |
| NYT Connections (extended) | — | 61.8% |
| ARC-AGI-1 | — | 63.7% |
| CritPt | — | 10% |
| Thematic Generalization | — | 61.7% |
| LiveBench Reasoning | 32.8% | — |
| LiveBench Data Analysis | 50% | — |
| ForecastBench | — | 57 |
| LiveBench | 41.3% | — |
| PIQA | 88.7% | — |
Math GPT-5.4 mini leads
GPT-4o mini: 10.4 (#314), GPT-5.4 mini: 45.5 (#75)
| Benchmark | GPT-4o mini | GPT-5.4 mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | 0.7% | 51.2% |
| OTIS Mock AIME 2024-2025 | 6.9% | 88.9% |
| LMArena Math | 1267 | 1419 |
| FrontierMath Tier 4 | — | 9.8% |
| ProofBench | — | 21% |
| Omni-MATH | 28% | — |
| LiveBench Math | 36.3% | — |
| MATH Level 5 | 52.6% | — |
| FrontierMath (Feb 2025 set) | — | 28.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
| GSM8K | 91.3% | — |
Knowledge GPT-5.4 mini leads
GPT-4o mini: 17.7 (#284), GPT-5.4 mini: 51.5 (#67)
| Benchmark | GPT-4o mini | GPT-5.4 mini |
|---|---|---|
| GPQA Diamond | 37.7% | 86.9% |
| SimpleQA Verified | 8.3% | 29.4% |
| LMArena Expert | 1235 | 1435 |
| MMLU-Pro | 60.3% | — |
| Confabulations | 37.2% | — |
| Vectara Hallucination Rate | — | 5.5% |
| GPQA (HELM) | 36.8% | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |
Multimodal GPT-5.4 mini leads
GPT-4o mini: 25.9 (#122), GPT-5.4 mini: 39.7 (#56)
| Benchmark | GPT-4o mini | GPT-5.4 mini |
|---|---|---|
| LMArena Vision | 1066 | 1245 |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
Multilingual GPT-5.4 mini leads
GPT-4o mini: 42.0 (#199), GPT-5.4 mini: 51.9 (#96)
| Benchmark | GPT-4o mini | GPT-5.4 mini |
|---|---|---|
| LMArena Non-English | 1266 | 1405 |
| LMArena Chinese | 1265 | 1446 |
| LMArena French | 1297 | 1440 |
| LMArena German | 1272 | 1409 |
| LMArena Japanese | 1216 | 1374 |
| LMArena Korean | 1195 | 1368 |
| LMArena Russian | 1275 | 1417 |
| LMArena Spanish | 1276 | 1405 |
Instruction Following GPT-5.4 mini leads
GPT-4o mini: 61.9 (#239), GPT-5.4 mini: 74.1 (#102)
| Benchmark | GPT-4o mini | GPT-5.4 mini |
|---|---|---|
| LMArena Instruction Following | 1258 | 1405 |
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |
Long Context GPT-5.4 mini leads
GPT-4o mini: 39.1 (#186), GPT-5.4 mini: 43.0 (#112)
| Benchmark | GPT-4o mini | GPT-5.4 mini |
|---|---|---|
| LMArena Longer Query | 1289 | 1407 |
Writing & Preference GPT-5.4 mini leads
GPT-4o mini: 39.5 (#248), GPT-5.4 mini: 64.0 (#58)
| Benchmark | GPT-4o mini | GPT-5.4 mini |
|---|---|---|
| LMArena Text | 1286 | 1412 |
| LMArena Creative Writing | 1268 | 1370 |
| EQ-Bench Creative Writing | 873 | 1665 |
| LMArena Multi-Turn | 1285 | 1429 |
| Short-Story Creative Writing | 67.2% | — |
| WildBench | 79.1% | — |
| LiveBench Language | 28.6% | — |
Frequently asked questions
Is GPT-4o mini better than GPT-5.4 mini?
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 25.5 on the Noometry Index. GPT-4o mini costs 6.4× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Which is cheaper, GPT-4o mini or GPT-5.4 mini?
GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GPT-5.4 mini lists at $0.75 and $4.50.
Is GPT-4o mini or GPT-5.4 mini better for coding?
GPT-5.4 mini scores higher on coding benchmarks: 45.2 versus 22.0 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 mini does, with 400K tokens against 128K.
How many benchmarks do GPT-4o mini and GPT-5.4 mini share?
31 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and GPT-5.4 mini has 46.