Model comparison
GPT-5.4 mini vs MiMo-V2-Omni
GPT-5.4 mini is the stronger model overall, scoring 44.8 to 42.9 on the Noometry Index. MiMo-V2-Omni costs 9.6× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. GPT-5.4 mini scores higher in 7 categories and MiMo-V2-Omni in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5.4 mini leads 51.4 to 39.9.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 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 262K.
Side by side
| GPT-5.4 mini | MiMo-V2-Omni | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 44.8 | 42.9 |
| Released | 2026-03-17 | 2026-03-18 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 262K |
| Max output | 128K | 131K |
| Input $ / M tokens | $0.75 | $0.14 |
| Output $ / M tokens | $4.50 | $0.28 |
| Results tracked | 46 | 18 |
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Category by category
Coding GPT-5.4 mini leads
GPT-5.4 mini: 45.0 (#67), MiMo-V2-Omni: 42.7 (#87)
| Benchmark | GPT-5.4 mini | MiMo-V2-Omni |
|---|---|---|
| LMArena Coding | 1438 | 1467 |
| FrontierCode | 27% | — |
| LMArena WebDev | 1397 | — |
| SciCode | 49.9% | — |
| WeirdML | 60.3% | — |
| ALE-Bench | 1,189 | — |
Agentic & Tool Use Not comparable
GPT-5.4 mini: 29.6 (#74), MiMo-V2-Omni: —
| Benchmark | GPT-5.4 mini | MiMo-V2-Omni |
|---|---|---|
| DeepResearch Bench | 36.3% | — |
Reasoning GPT-5.4 mini leads
GPT-5.4 mini: 30.3 (#77), MiMo-V2-Omni: 28.6 (#86)
| Benchmark | GPT-5.4 mini | MiMo-V2-Omni |
|---|---|---|
| LMArena Hard Prompts | 1424 | 1445 |
| ARC-AGI-2 | 18.9% | — |
| Kagi LLM Benchmark | 37.9% | — |
| NYT Connections (extended) | 61.8% | — |
| ARC-AGI-1 | 63.7% | — |
| CritPt | 10% | — |
| Chess Puzzles | 24% | — |
| Thematic Generalization | 61.7% | — |
| Mystery Game Puzzles | 11% | — |
| DTBench | 80% | — |
| LMCA | 40.8% | — |
| Epoch Capabilities Index | 148.83 | — |
| ForecastBench | 57 | — |
Math GPT-5.4 mini leads
GPT-5.4 mini: 45.4 (#63), MiMo-V2-Omni: 36.4 (#112)
| Benchmark | GPT-5.4 mini | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | 1418 | 1432 |
| FrontierMath (Tiers 1-3) | 51.2% | — |
| FrontierMath Tier 4 | 9.8% | — |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| ProofBench | 21% | — |
| FrontierMath (Feb 2025 set) | 28.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GPT-5.4 mini leads
GPT-5.4 mini: 51.4 (#62), MiMo-V2-Omni: 39.9 (#114)
| Benchmark | GPT-5.4 mini | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | 1434 | 1449 |
| GPQA Diamond | 86.9% | — |
| SimpleQA Verified | 29.4% | — |
| Vectara Hallucination Rate | 5.5% | — |
Multimodal GPT-5.4 mini leads
GPT-5.4 mini: 39.0 (#51), MiMo-V2-Omni: 37.9 (#62)
| Benchmark | GPT-5.4 mini | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | 1245 | 1228 |
Multilingual Too close to call
GPT-5.4 mini: 52.1 (#94), MiMo-V2-Omni: 52.0 (#97)
| Benchmark | GPT-5.4 mini | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | 1405 | 1404 |
| LMArena Chinese | 1446 | 1469 |
| LMArena French | 1440 | 1448 |
| LMArena German | 1407 | 1398 |
| LMArena Japanese | 1375 | 1318 |
| LMArena Korean | 1369 | 1355 |
| LMArena Russian | 1417 | 1412 |
| LMArena Spanish | 1403 | 1432 |
Instruction Following MiMo-V2-Omni leads
GPT-5.4 mini: 74.3 (#99), MiMo-V2-Omni: 75.4 (#62)
| Benchmark | GPT-5.4 mini | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | 1405 | 1428 |
Long Context MiMo-V2-Omni leads
GPT-5.4 mini: 42.9 (#107), MiMo-V2-Omni: 44.1 (#72)
| Benchmark | GPT-5.4 mini | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | 1407 | 1442 |
Writing & Preference GPT-5.4 mini leads
GPT-5.4 mini: 64.2 (#56), MiMo-V2-Omni: 61.6 (#83)
| Benchmark | GPT-5.4 mini | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | 1411 | 1424 |
| LMArena Creative Writing | 1370 | 1393 |
| LMArena Multi-Turn | 1429 | 1446 |
| EQ-Bench Creative Writing | 1665 | — |
Frequently asked questions
Is GPT-5.4 mini better than MiMo-V2-Omni?
GPT-5.4 mini is the stronger model overall, scoring 44.8 to 42.9 on the Noometry Index. MiMo-V2-Omni costs 9.6× 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-5.4 mini or MiMo-V2-Omni?
MiMo-V2-Omni is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; GPT-5.4 mini lists at $0.75 and $4.50.
Is GPT-5.4 mini or MiMo-V2-Omni better for coding?
GPT-5.4 mini scores higher on coding benchmarks: 45.0 versus 42.7 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 mini does, with 400K tokens against 262K.
How many benchmarks do GPT-5.4 mini and MiMo-V2-Omni share?
18 benchmarks have published results for both models. GPT-5.4 mini has 46 scored results on Noometry and MiMo-V2-Omni has 18.