Model comparison
GPT-5.4 Pro vs MiMo-V2-Omni
GPT-5.4 Pro is the stronger model overall, scoring 58.9 to 43.6 on the Noometry Index. MiMo-V2-Omni costs 386× less per token, which makes it the better buy when GPT-5.4 Pro's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in reasoning, where GPT-5.4 Pro leads 70.7 to 29.7.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $30 / $180 for GPT-5.4 Pro.
- GPT-5.4 Pro accepts more context: 1.05M tokens versus 262K.
Side by side
| GPT-5.4 Pro | MiMo-V2-Omni | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 58.9 | 43.6 |
| Released | 2026-03-05 | 2026-03-18 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 262K |
| Max output | 128K | 131K |
| Input $ / M tokens | $30 | $0.14 |
| Output $ / M tokens | $180 | $0.28 |
| Results tracked | 16 | 18 |
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Category by category
Coding Too close to call
GPT-5.4 Pro: 43.2 (#90), MiMo-V2-Omni: 43.3 (#89)
| Benchmark | GPT-5.4 Pro | MiMo-V2-Omni |
|---|---|---|
| WeirdML | 57.4% | — |
| LMArena Coding | — | 1466 |
Reasoning GPT-5.4 Pro leads
GPT-5.4 Pro: 70.7 (#13), MiMo-V2-Omni: 29.7 (#88)
| Benchmark | GPT-5.4 Pro | MiMo-V2-Omni |
|---|---|---|
| ARC-AGI-2 | 83.3% | — |
| SimpleBench | 74.1% | — |
| ARC-AGI-1 | 94.5% | — |
| CritPt | 30% | — |
| Chess Puzzles | 58.6% | — |
| EnigmaEval | 23.8% | — |
| LMArena Hard Prompts | — | 1445 |
| Epoch Capabilities Index | 158.93 | — |
Math GPT-5.4 Pro leads
GPT-5.4 Pro: 72.4 (#22), MiMo-V2-Omni: 39.1 (#115)
| Benchmark | GPT-5.4 Pro | MiMo-V2-Omni |
|---|---|---|
| FrontierMath (Tiers 1-3) | 82.5% | — |
| FrontierMath Tier 4 | 58.5% | — |
| LMArena Math | — | 1430 |
| FrontierMath (Feb 2025 set) | 50% | — |
| FrontierMath Tier 4 (v1) | 37.5% | — |
Knowledge GPT-5.4 Pro leads
GPT-5.4 Pro: 68.3 (#7), MiMo-V2-Omni: 40.5 (#118)
| Benchmark | GPT-5.4 Pro | MiMo-V2-Omni |
|---|---|---|
| GPQA Diamond | 94.6% | — |
| Humanity's Last Exam | 44.3% | — |
| SimpleQA Verified | 46.3% | — |
| Vectara Hallucination Rate | 8.3% | — |
| LMArena Expert | — | 1449 |
Multimodal Not comparable
GPT-5.4 Pro: —, MiMo-V2-Omni: 38.6 (#63)
| Benchmark | GPT-5.4 Pro | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | — | 1228 |
Multilingual Not comparable
GPT-5.4 Pro: —, MiMo-V2-Omni: 51.8 (#102)
| Benchmark | GPT-5.4 Pro | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | — | 1404 |
| LMArena Chinese | — | 1465 |
| LMArena French | — | 1447 |
| LMArena German | — | 1399 |
| LMArena Japanese | — | 1317 |
| LMArena Korean | — | 1355 |
| LMArena Russian | — | 1412 |
| LMArena Spanish | — | 1434 |
Instruction Following Not comparable
GPT-5.4 Pro: —, MiMo-V2-Omni: 75.2 (#66)
| Benchmark | GPT-5.4 Pro | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | — | 1428 |
Long Context Not comparable
GPT-5.4 Pro: —, MiMo-V2-Omni: 44.1 (#76)
| Benchmark | GPT-5.4 Pro | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | — | 1442 |
Writing & Preference Not comparable
GPT-5.4 Pro: —, MiMo-V2-Omni: 61.4 (#87)
| Benchmark | GPT-5.4 Pro | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | — | 1423 |
| LMArena Creative Writing | — | 1392 |
| LMArena Multi-Turn | — | 1445 |
Frequently asked questions
Is GPT-5.4 Pro better than MiMo-V2-Omni?
GPT-5.4 Pro is the stronger model overall, scoring 58.9 to 43.6 on the Noometry Index. MiMo-V2-Omni costs 386× less per token, which makes it the better buy when GPT-5.4 Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5.4 Pro 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 Pro lists at $30 and $180.
Is GPT-5.4 Pro or MiMo-V2-Omni better for coding?
They score almost the same on coding (43.2 vs 43.3); test both on your own repository before choosing.
Which has the bigger context window?
GPT-5.4 Pro does, with 1.05M tokens against 262K.
How many benchmarks do GPT-5.4 Pro and MiMo-V2-Omni share?
0 benchmarks have published results for both models. GPT-5.4 Pro has 16 scored results on Noometry and MiMo-V2-Omni has 18.