Model comparison
GPT-5.4 nano vs MiMo-V2-Flash
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 40.8 on the Noometry Index. MiMo-V2-Flash costs 2.6× less per token, which makes it the better buy when GPT-5.4 nano's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. GPT-5.4 nano scores higher in 3 categories and MiMo-V2-Flash in 5 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-5.4 nano leads 43.1 to 35.8.
- The biggest single-benchmark swing is SciCode: 46.9% for GPT-5.4 nano and 25.9% for MiMo-V2-Flash.
- MiMo-V2-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.20 / $1.25 for GPT-5.4 nano.
- GPT-5.4 nano accepts more context: 400K tokens versus 262K.
- MiMo-V2-Flash has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 nano | MiMo-V2-Flash | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 41.9 | 40.8 |
| Released | 2026-03-17 | 2025-12-16 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.20 | $0.14 |
| Output $ / M tokens | $1.25 | $0.28 |
| Results tracked | 40 | 21 |
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Category by category
Coding GPT-5.4 nano leads
GPT-5.4 nano: 43.1 (#82), MiMo-V2-Flash: 35.8 (#205)
| Benchmark | GPT-5.4 nano | MiMo-V2-Flash |
|---|---|---|
| SciCode | 46.9% | 25.9% |
| LMArena Coding | 1404 | 1443 |
| ALE-Bench | 1,005 | 737.95 |
| LMArena WebDev | — | 1330 |
| WeirdML | 49.2% | — |
Reasoning Too close to call
GPT-5.4 nano: 23.8 (#159), MiMo-V2-Flash: 24.1 (#155)
| Benchmark | GPT-5.4 nano | MiMo-V2-Flash |
|---|---|---|
| CritPt | 9.3% | 0% |
| LMArena Hard Prompts | 1380 | 1420 |
| ARC-AGI-2 | 5.7% | — |
| Kagi LLM Benchmark | 39.7% | — |
| ARC-AGI-1 | 51.5% | — |
| Chess Puzzles | 30% | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 80.3% | — |
| LMCA | 36.9% | — |
| Epoch Capabilities Index | 145.78 | — |
| ForecastBench | 57.3 | — |
Math GPT-5.4 nano leads
GPT-5.4 nano: 40.7 (#76), MiMo-V2-Flash: 35.6 (#141)
| Benchmark | GPT-5.4 nano | MiMo-V2-Flash |
|---|---|---|
| LMArena Math | 1406 | 1396 |
| FrontierMath (Tiers 1-3) | 44.9% | — |
| FrontierMath Tier 4 | 12.2% | — |
| OTIS Mock AIME 2024-2025 | 87.8% | — |
| ProofBench | 5% | — |
| FrontierMath (Feb 2025 set) | 25.9% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |
Knowledge GPT-5.4 nano leads
GPT-5.4 nano: 41.8 (#94), MiMo-V2-Flash: 39.1 (#126)
| Benchmark | GPT-5.4 nano | MiMo-V2-Flash |
|---|---|---|
| LMArena Expert | 1397 | 1425 |
| GPQA Diamond | 78.5% | — |
| SimpleQA Verified | 11.7% | — |
| Vectara Hallucination Rate | 3.1% | — |
Multimodal Not comparable
GPT-5.4 nano: 36.0 (#73), MiMo-V2-Flash: —
| Benchmark | GPT-5.4 nano | MiMo-V2-Flash |
|---|---|---|
| LMArena Vision | 1196 | — |
Multilingual MiMo-V2-Flash leads
GPT-5.4 nano: 48.8 (#136), MiMo-V2-Flash: 51.1 (#109)
| Benchmark | GPT-5.4 nano | MiMo-V2-Flash |
|---|---|---|
| LMArena Non-English | 1359 | 1391 |
| LMArena Chinese | 1391 | 1463 |
| LMArena French | 1396 | 1429 |
| LMArena German | 1368 | 1395 |
| LMArena Japanese | 1342 | 1324 |
| LMArena Korean | 1321 | 1358 |
| LMArena Russian | 1363 | 1387 |
| LMArena Spanish | 1368 | 1420 |
Instruction Following MiMo-V2-Flash leads
GPT-5.4 nano: 72.1 (#139), MiMo-V2-Flash: 73.7 (#115)
| Benchmark | GPT-5.4 nano | MiMo-V2-Flash |
|---|---|---|
| LMArena Instruction Following | 1362 | 1392 |
Long Context MiMo-V2-Flash leads
GPT-5.4 nano: 41.6 (#131), MiMo-V2-Flash: 43.0 (#106)
| Benchmark | GPT-5.4 nano | MiMo-V2-Flash |
|---|---|---|
| LMArena Longer Query | 1365 | 1409 |
Writing & Preference MiMo-V2-Flash leads
GPT-5.4 nano: 55.9 (#137), MiMo-V2-Flash: 59.9 (#101)
| Benchmark | GPT-5.4 nano | MiMo-V2-Flash |
|---|---|---|
| LMArena Text | 1372 | 1411 |
| LMArena Creative Writing | 1313 | 1375 |
| LMArena Multi-Turn | 1382 | 1404 |
Frequently asked questions
Is GPT-5.4 nano better than MiMo-V2-Flash?
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 40.8 on the Noometry Index. MiMo-V2-Flash costs 2.6× less per token, which makes it the better buy when GPT-5.4 nano's lead doesn't matter for your workload.
Which is cheaper, GPT-5.4 nano or MiMo-V2-Flash?
MiMo-V2-Flash is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; GPT-5.4 nano lists at $0.20 and $1.25.
Is GPT-5.4 nano or MiMo-V2-Flash better for coding?
GPT-5.4 nano scores higher on coding benchmarks: 43.1 versus 35.8 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 nano does, with 400K tokens against 262K.
How many benchmarks do GPT-5.4 nano and MiMo-V2-Flash share?
20 benchmarks have published results for both models. GPT-5.4 nano has 40 scored results on Noometry and MiMo-V2-Flash has 21.