Model comparison
GPT-4.1 nano vs MiMo-V2.5-Pro
MiMo-V2.5-Pro is the stronger model overall, scoring 44.8 to 27.7 on the Noometry Index. GPT-4.1 nano costs 3.1× less per token, which makes it the better buy when MiMo-V2.5-Pro's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
Summary
- They share 19 benchmarks with published results for both. GPT-4.1 nano scores higher in 0 categories and MiMo-V2.5-Pro in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2.5-Pro leads 65.5 to 40.7.
- The biggest single-benchmark swing is DTBench: 52.5% for GPT-4.1 nano and 84.5% for MiMo-V2.5-Pro.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2.5-Pro.
- MiMo-V2.5-Pro accepts more context: 1.05M tokens versus 1.05M.
- MiMo-V2.5-Pro has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 nano | MiMo-V2.5-Pro | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 27.7 | 44.8 |
| Released | 2025-04-14 | 2026-04-22 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 1.05M |
| Max output | 33K | 131K |
| Input $ / M tokens | $0.10 | $0.43 |
| Output $ / M tokens | $0.40 | $0.87 |
| Results tracked | 38 | 27 |
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Category by category
Coding MiMo-V2.5-Pro leads
GPT-4.1 nano: 23.8 (#325), MiMo-V2.5-Pro: 47.0 (#58)
| Benchmark | GPT-4.1 nano | MiMo-V2.5-Pro |
|---|---|---|
| SciCode | 25.9% | 50.2% |
| LMArena Coding | 1306 | 1502 |
| Aider Polyglot | 8.9% | — |
| LMArena WebDev | — | 1477 |
| WeirdML | 19% | — |
| ALE-Bench | — | 899.8 |
Agentic & Tool Use Not comparable
GPT-4.1 nano: 26.3 (#98), MiMo-V2.5-Pro: —
| Benchmark | GPT-4.1 nano | MiMo-V2.5-Pro |
|---|---|---|
| Berkeley Function Calling Leaderboard | 33% | — |
Reasoning MiMo-V2.5-Pro leads
GPT-4.1 nano: 8.6 (#344), MiMo-V2.5-Pro: 25.9 (#124)
| Benchmark | GPT-4.1 nano | MiMo-V2.5-Pro |
|---|---|---|
| CritPt | 0% | 4% |
| LMArena Hard Prompts | 1286 | 1487 |
| DTBench | 52.5% | 84.5% |
| LMCA | 5.5% | 29.5% |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 33.3% | — |
| NYT Connections (extended) | — | 34.4% |
| ARC-AGI-1 | 0% | — |
| Epoch Capabilities Index | 129.62 | — |
Math MiMo-V2.5-Pro leads
GPT-4.1 nano: 25.5 (#246), MiMo-V2.5-Pro: 38.6 (#84)
| Benchmark | GPT-4.1 nano | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Math | 1274 | 1480 |
| OTIS Mock AIME 2024-2025 | 28.9% | — |
| ProofBench | — | 22% |
| Omni-MATH | 36.7% | — |
| MATH Level 5 | 70% | — |
| FrontierMath (Feb 2025 set) | 1% | — |
Knowledge MiMo-V2.5-Pro leads
GPT-4.1 nano: 21.8 (#268), MiMo-V2.5-Pro: 41.5 (#100)
| Benchmark | GPT-4.1 nano | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Expert | 1272 | 1501 |
| GPQA Diamond | 48.9% | — |
| SimpleQA Verified | 6% | — |
| MMLU-Pro | 55% | — |
| GPQA (HELM) | 50.7% | — |
Multimodal Not comparable
GPT-4.1 nano: 28.6 (#108), MiMo-V2.5-Pro: —
| Benchmark | GPT-4.1 nano | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Vision | 1063 | — |
Multilingual MiMo-V2.5-Pro leads
GPT-4.1 nano: 41.8 (#200), MiMo-V2.5-Pro: 55.3 (#33)
| Benchmark | GPT-4.1 nano | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Non-English | 1260 | 1449 |
| LMArena Chinese | 1270 | 1507 |
| LMArena German | 1288 | 1455 |
| LMArena Japanese | 1199 | 1418 |
| LMArena Russian | 1261 | 1450 |
| LMArena French | — | 1489 |
| LMArena Korean | — | 1436 |
| LMArena Spanish | — | 1470 |
Instruction Following MiMo-V2.5-Pro leads
GPT-4.1 nano: 68.0 (#188), MiMo-V2.5-Pro: 77.6 (#21)
| Benchmark | GPT-4.1 nano | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Instruction Following | 1267 | 1477 |
| IFEval | 84.3% | — |
Long Context MiMo-V2.5-Pro leads
GPT-4.1 nano: 23.7 (#291), MiMo-V2.5-Pro: 45.4 (#38)
| Benchmark | GPT-4.1 nano | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Longer Query | 1283 | 1482 |
| Fiction.LiveBench | 25% | — |
Writing & Preference MiMo-V2.5-Pro leads
GPT-4.1 nano: 40.7 (#238), MiMo-V2.5-Pro: 65.5 (#47)
| Benchmark | GPT-4.1 nano | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Text | 1285 | 1465 |
| LMArena Creative Writing | 1260 | 1440 |
| EQ-Bench Creative Writing | 946 | 1493 |
| LMArena Multi-Turn | 1277 | 1477 |
| WildBench | 81.2% | — |
| EQ-Bench 4 | — | 1208 |
Frequently asked questions
Is GPT-4.1 nano better than MiMo-V2.5-Pro?
MiMo-V2.5-Pro is the stronger model overall, scoring 44.8 to 27.7 on the Noometry Index. GPT-4.1 nano costs 3.1× less per token, which makes it the better buy when MiMo-V2.5-Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 nano or MiMo-V2.5-Pro?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; MiMo-V2.5-Pro lists at $0.43 and $0.87.
Is GPT-4.1 nano or MiMo-V2.5-Pro better for coding?
MiMo-V2.5-Pro scores higher on coding benchmarks: 47.0 versus 23.8 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.5-Pro does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-4.1 nano and MiMo-V2.5-Pro share?
19 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and MiMo-V2.5-Pro has 27.