Model comparison
GPT-5 Nano vs MiMo-V2-Pro
MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 33.5 on the Noometry Index. GPT-5 Nano costs 4.0× less per token, which makes it the better buy when MiMo-V2-Pro's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. GPT-5 Nano scores higher in 0 categories and MiMo-V2-Pro in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2-Pro leads 62.8 to 39.1.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2-Pro.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 400K.
Side by side
| GPT-5 Nano | MiMo-V2-Pro | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 33.5 | 43.0 |
| Released | 2025-08-07 | 2026-03-18 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $0.05 | $0.43 |
| Output $ / M tokens | $0.40 | $0.87 |
| Results tracked | 49 | 23 |
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Category by category
Coding MiMo-V2-Pro leads
GPT-5 Nano: 33.6 (#254), MiMo-V2-Pro: 43.8 (#83)
| Benchmark | GPT-5 Nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Coding | 1351 | 1476 |
| ALE-Bench | 718.67 | 785.17 |
| SWE-bench Verified (bash only) | 34.8% | — |
| LMArena WebDev | — | 1433 |
| WeirdML | 38.1% | — |
Agentic & Tool Use Not comparable
GPT-5 Nano: 25.8 (#106), MiMo-V2-Pro: —
| Benchmark | GPT-5 Nano | MiMo-V2-Pro |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |
Reasoning MiMo-V2-Pro leads
GPT-5 Nano: 16.3 (#306), MiMo-V2-Pro: 22.1 (#206)
| Benchmark | GPT-5 Nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Hard Prompts | 1328 | 1457 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| NYT Connections (extended) | — | 25.8% |
| ARC-AGI-1 | 20.7% | — |
| Chess Puzzles | 27% | — |
| Thematic Generalization | — | 45.9% |
| Mystery Game Puzzles | 9% | — |
| DTBench | 62.7% | — |
| LMCA | 7.9% | — |
| Epoch Capabilities Index | 139.38 | — |
| ForecastBench | 59.1 | — |
Math MiMo-V2-Pro leads
GPT-5 Nano: 29.4 (#241), MiMo-V2-Pro: 39.5 (#102)
| Benchmark | GPT-5 Nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1317 | 1447 |
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 81.1% | — |
| ProofBench | 12% | — |
| Omni-MATH | 54.6% | — |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge MiMo-V2-Pro leads
GPT-5 Nano: 35.9 (#178), MiMo-V2-Pro: 41.4 (#111)
| Benchmark | GPT-5 Nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1321 | 1478 |
| GPQA Diamond | 69.4% | — |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
Multimodal Not comparable
GPT-5 Nano: 31.3 (#108), MiMo-V2-Pro: —
| Benchmark | GPT-5 Nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Vision | 1159 | — |
| VPCT | 37.2% | — |
Multilingual MiMo-V2-Pro leads
GPT-5 Nano: 45.3 (#172), MiMo-V2-Pro: 52.7 (#81)
| Benchmark | GPT-5 Nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1313 | 1416 |
| LMArena Chinese | 1356 | 1456 |
| LMArena German | 1327 | 1417 |
| LMArena Japanese | 1226 | 1366 |
| LMArena Korean | 1269 | 1400 |
| LMArena Russian | 1296 | 1427 |
| LMArena Spanish | 1360 | 1457 |
| LMArena French | — | 1469 |
Instruction Following MiMo-V2-Pro leads
GPT-5 Nano: 75.0 (#79), MiMo-V2-Pro: 76.0 (#49)
| Benchmark | GPT-5 Nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1306 | 1445 |
| IFEval | 93.2% | — |
Long Context MiMo-V2-Pro leads
GPT-5 Nano: 31.3 (#281), MiMo-V2-Pro: 41.5 (#138)
| Benchmark | GPT-5 Nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1312 | 1455 |
| Fiction.LiveBench | 44.4% | — |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |
Writing & Preference MiMo-V2-Pro leads
GPT-5 Nano: 39.1 (#249), MiMo-V2-Pro: 62.8 (#70)
| Benchmark | GPT-5 Nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1320 | 1436 |
| LMArena Creative Writing | 1249 | 1415 |
| LMArena Multi-Turn | 1311 | 1456 |
| EQ-Bench Creative Writing | 705 | — |
| WildBench | 80.6% | — |
Frequently asked questions
Is GPT-5 Nano better than MiMo-V2-Pro?
MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 33.5 on the Noometry Index. GPT-5 Nano costs 4.0× less per token, which makes it the better buy when MiMo-V2-Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5 Nano or MiMo-V2-Pro?
GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; MiMo-V2-Pro lists at $0.43 and $0.87.
Is GPT-5 Nano or MiMo-V2-Pro better for coding?
MiMo-V2-Pro scores higher on coding benchmarks: 43.8 versus 33.6 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Pro does, with 1.05M tokens against 400K.
How many benchmarks do GPT-5 Nano and MiMo-V2-Pro share?
17 benchmarks have published results for both models. GPT-5 Nano has 49 scored results on Noometry and MiMo-V2-Pro has 23.