Model comparison
GPT-5 Nano vs MiMo-V2.6-Pro
MiMo-V2.6-Pro is the stronger model overall, scoring 50.3 to 33.5 on the Noometry Index. GPT-5 Nano costs 4.0× less per token, which makes it the better buy when MiMo-V2.6-Pro's lead doesn't matter for your workload.
Last verified . 15 shared benchmarks.
Summary
- They share 15 benchmarks with published results for both. GPT-5 Nano scores higher in 0 categories and MiMo-V2.6-Pro in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2.6-Pro leads 66.8 to 39.1.
- The biggest single-benchmark swing is ProofBench: 12% for GPT-5 Nano and 70% for MiMo-V2.6-Pro.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2.6-Pro.
- 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 Nano | MiMo-V2.6-Pro | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 33.5 | 50.3 |
| Released | 2025-08-07 | 2026-09-21 |
| Weights | Proprietary | Open |
| 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 | 19 |
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Category by category
Coding MiMo-V2.6-Pro leads
GPT-5 Nano: 33.6 (#254), MiMo-V2.6-Pro: 55.5 (#23)
| Benchmark | GPT-5 Nano | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Coding | 1351 | 1534 |
| ALE-Bench | 718.67 | 1,158 |
| SWE-bench Verified (bash only) | 34.8% | — |
| LMArena WebDev | — | 1629 |
| SciCode | — | 60.9% |
| WeirdML | 38.1% | — |
Agentic & Tool Use MiMo-V2.6-Pro leads
GPT-5 Nano: 25.8 (#106), MiMo-V2.6-Pro: 37.5 (#35)
| Benchmark | GPT-5 Nano | MiMo-V2.6-Pro |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| APEX-Agents | — | 59.5% |
| Berkeley Function Calling Leaderboard | 51.5% | — |
Reasoning MiMo-V2.6-Pro leads
GPT-5 Nano: 16.3 (#306), MiMo-V2.6-Pro: 43.1 (#50)
| Benchmark | GPT-5 Nano | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Hard Prompts | 1328 | 1512 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| ARC-AGI-1 | 20.7% | — |
| CritPt | — | 26.6% |
| Chess Puzzles | 27% | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 62.7% | — |
| LMCA | 7.9% | — |
| Epoch Capabilities Index | 139.38 | — |
| ForecastBench | 59.1 | — |
Math MiMo-V2.6-Pro leads
GPT-5 Nano: 29.4 (#241), MiMo-V2.6-Pro: 54.5 (#45)
| Benchmark | GPT-5 Nano | MiMo-V2.6-Pro |
|---|---|---|
| ProofBench | 12% | 70% |
| LMArena Math | 1317 | 1494 |
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 81.1% | — |
| Omni-MATH | 54.6% | — |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge MiMo-V2.6-Pro leads
GPT-5 Nano: 35.9 (#178), MiMo-V2.6-Pro: 43.5 (#92)
| Benchmark | GPT-5 Nano | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Expert | 1321 | 1543 |
| GPQA Diamond | 69.4% | — |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
Multimodal MiMo-V2.6-Pro leads
GPT-5 Nano: 31.3 (#108), MiMo-V2.6-Pro: 40.8 (#43)
| Benchmark | GPT-5 Nano | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Vision | 1159 | 1264 |
| VPCT | 37.2% | — |
Multilingual MiMo-V2.6-Pro leads
GPT-5 Nano: 45.3 (#172), MiMo-V2.6-Pro: 56.9 (#14)
| Benchmark | GPT-5 Nano | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Non-English | 1313 | 1474 |
| LMArena Chinese | 1356 | 1529 |
| LMArena Russian | 1296 | 1480 |
| LMArena German | 1327 | — |
| LMArena Japanese | 1226 | — |
| LMArena Korean | 1269 | — |
| LMArena Spanish | 1360 | — |
Instruction Following MiMo-V2.6-Pro leads
GPT-5 Nano: 75.0 (#79), MiMo-V2.6-Pro: 78.2 (#12)
| Benchmark | GPT-5 Nano | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Instruction Following | 1306 | 1493 |
| IFEval | 93.2% | — |
Long Context MiMo-V2.6-Pro leads
GPT-5 Nano: 31.3 (#281), MiMo-V2.6-Pro: 46.0 (#27)
| Benchmark | GPT-5 Nano | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Longer Query | 1312 | 1501 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference MiMo-V2.6-Pro leads
GPT-5 Nano: 39.1 (#249), MiMo-V2.6-Pro: 66.8 (#33)
| Benchmark | GPT-5 Nano | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Text | 1320 | 1492 |
| LMArena Creative Writing | 1249 | 1468 |
| LMArena Multi-Turn | 1311 | 1464 |
| EQ-Bench Creative Writing | 705 | — |
| WildBench | 80.6% | — |
Frequently asked questions
Is GPT-5 Nano better than MiMo-V2.6-Pro?
MiMo-V2.6-Pro is the stronger model overall, scoring 50.3 to 33.5 on the Noometry Index. GPT-5 Nano costs 4.0× less per token, which makes it the better buy when MiMo-V2.6-Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5 Nano or MiMo-V2.6-Pro?
GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; MiMo-V2.6-Pro lists at $0.43 and $0.87.
Is GPT-5 Nano or MiMo-V2.6-Pro better for coding?
MiMo-V2.6-Pro scores higher on coding benchmarks: 55.5 versus 33.6 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 Nano and MiMo-V2.6-Pro share?
15 benchmarks have published results for both models. GPT-5 Nano has 49 scored results on Noometry and MiMo-V2.6-Pro has 19.