Model comparison
GPT-5.4 mini vs MiMo-V2.6-Pro
MiMo-V2.6-Pro is the stronger model overall, scoring 46.7 to 44.8 on the Noometry Index.
Last verified . 14 shared benchmarks.
Summary
- They share 14 benchmarks with published results for both. GPT-5.4 mini scores higher in 2 categories and MiMo-V2.6-Pro in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5.4 mini leads 51.4 to 43.0.
- MiMo-V2.6-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.75 / $4.50 for GPT-5.4 mini.
- MiMo-V2.6-Pro accepts more context: 1.05M tokens versus 400K.
- MiMo-V2.6-Pro has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 mini | MiMo-V2.6-Pro | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 44.8 | 46.7 |
| Released | 2026-03-17 | 2026-09-22 |
| Weights | Proprietary | Open |
| Context window | 400K | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $0.75 | $0.43 |
| Output $ / M tokens | $4.50 | $0.87 |
| Results tracked | 46 | 14 |
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Category by category
Coding MiMo-V2.6-Pro leads
GPT-5.4 mini: 45.0 (#67), MiMo-V2.6-Pro: 53.2 (#27)
| Benchmark | GPT-5.4 mini | MiMo-V2.6-Pro |
|---|---|---|
| LMArena WebDev | 1397 | 1618 |
| LMArena Coding | 1438 | 1538 |
| FrontierCode | 27% | — |
| SciCode | 49.9% | — |
| WeirdML | 60.3% | — |
| ALE-Bench | 1,189 | — |
Agentic & Tool Use Not comparable
GPT-5.4 mini: 29.6 (#74), MiMo-V2.6-Pro: —
| Benchmark | GPT-5.4 mini | MiMo-V2.6-Pro |
|---|---|---|
| DeepResearch Bench | 36.3% | — |
Reasoning Too close to call
GPT-5.4 mini: 30.3 (#77), MiMo-V2.6-Pro: 30.4 (#76)
| Benchmark | GPT-5.4 mini | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Hard Prompts | 1424 | 1511 |
| 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-V2.6-Pro: 37.9 (#91)
| Benchmark | GPT-5.4 mini | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Math | 1418 | 1497 |
| 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-V2.6-Pro: 43.0 (#85)
| Benchmark | GPT-5.4 mini | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Expert | 1434 | 1548 |
| GPQA Diamond | 86.9% | — |
| SimpleQA Verified | 29.4% | — |
| Vectara Hallucination Rate | 5.5% | — |
Multimodal MiMo-V2.6-Pro leads
GPT-5.4 mini: 39.0 (#51), MiMo-V2.6-Pro: 40.2 (#40)
| Benchmark | GPT-5.4 mini | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Vision | 1245 | 1265 |
Multilingual MiMo-V2.6-Pro leads
GPT-5.4 mini: 52.1 (#94), MiMo-V2.6-Pro: 57.0 (#15)
| Benchmark | GPT-5.4 mini | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Non-English | 1405 | 1474 |
| LMArena Chinese | 1446 | 1532 |
| LMArena Russian | 1417 | 1481 |
| LMArena French | 1440 | — |
| LMArena German | 1407 | — |
| LMArena Japanese | 1375 | — |
| LMArena Korean | 1369 | — |
| LMArena Spanish | 1403 | — |
Instruction Following MiMo-V2.6-Pro leads
GPT-5.4 mini: 74.3 (#99), MiMo-V2.6-Pro: 78.2 (#10)
| Benchmark | GPT-5.4 mini | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Instruction Following | 1405 | 1490 |
Long Context MiMo-V2.6-Pro leads
GPT-5.4 mini: 42.9 (#107), MiMo-V2.6-Pro: 46.0 (#26)
| Benchmark | GPT-5.4 mini | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Longer Query | 1407 | 1500 |
Writing & Preference MiMo-V2.6-Pro leads
GPT-5.4 mini: 64.2 (#56), MiMo-V2.6-Pro: 66.9 (#32)
| Benchmark | GPT-5.4 mini | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Text | 1411 | 1491 |
| LMArena Creative Writing | 1370 | 1465 |
| LMArena Multi-Turn | 1429 | 1463 |
| EQ-Bench Creative Writing | 1665 | — |
Frequently asked questions
Is GPT-5.4 mini better than MiMo-V2.6-Pro?
MiMo-V2.6-Pro is the stronger model overall, scoring 46.7 to 44.8 on the Noometry Index.
Which is cheaper, GPT-5.4 mini or MiMo-V2.6-Pro?
MiMo-V2.6-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; GPT-5.4 mini lists at $0.75 and $4.50.
Is GPT-5.4 mini or MiMo-V2.6-Pro better for coding?
MiMo-V2.6-Pro scores higher on coding benchmarks: 53.2 versus 45.0 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.6-Pro does, with 1.05M tokens against 400K.
How many benchmarks do GPT-5.4 mini and MiMo-V2.6-Pro share?
14 benchmarks have published results for both models. GPT-5.4 mini has 46 scored results on Noometry and MiMo-V2.6-Pro has 14.