Model comparison
GPT-4.1 nano vs MiMo-V2-Pro
MiMo-V2-Pro is the stronger model overall, scoring 42.4 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-Pro's lead doesn't matter for your workload.
Last verified . 14 shared benchmarks.
Summary
- They share 14 benchmarks with published results for both. GPT-4.1 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 62.9 to 40.7.
- GPT-4.1 nano is cheaper at $0.10 / $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 1.05M.
Side by side
| GPT-4.1 nano | MiMo-V2-Pro | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 27.7 | 42.4 |
| Released | 2025-04-14 | 2026-03-18 |
| Weights | Proprietary | Proprietary |
| 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 | 23 |
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Category by category
Coding MiMo-V2-Pro leads
GPT-4.1 nano: 23.8 (#325), MiMo-V2-Pro: 43.4 (#76)
| Benchmark | GPT-4.1 nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Coding | 1306 | 1476 |
| Aider Polyglot | 8.9% | — |
| LMArena WebDev | — | 1433 |
| SciCode | 25.9% | — |
| WeirdML | 19% | — |
| ALE-Bench | — | 785.17 |
Agentic & Tool Use Not comparable
GPT-4.1 nano: 26.3 (#98), MiMo-V2-Pro: —
| Benchmark | GPT-4.1 nano | MiMo-V2-Pro |
|---|---|---|
| Berkeley Function Calling Leaderboard | 33% | — |
Reasoning MiMo-V2-Pro leads
GPT-4.1 nano: 8.6 (#344), MiMo-V2-Pro: 21.3 (#200)
| Benchmark | GPT-4.1 nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Hard Prompts | 1286 | 1457 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 33.3% | — |
| NYT Connections (extended) | — | 25.8% |
| ARC-AGI-1 | 0% | — |
| CritPt | 0% | — |
| Thematic Generalization | — | 45.9% |
| DTBench | 52.5% | — |
| LMCA | 5.5% | — |
| Epoch Capabilities Index | 129.62 | — |
Math MiMo-V2-Pro leads
GPT-4.1 nano: 25.5 (#246), MiMo-V2-Pro: 36.7 (#104)
| Benchmark | GPT-4.1 nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1274 | 1447 |
| OTIS Mock AIME 2024-2025 | 28.9% | — |
| Omni-MATH | 36.7% | — |
| MATH Level 5 | 70% | — |
| FrontierMath (Feb 2025 set) | 1% | — |
Knowledge MiMo-V2-Pro leads
GPT-4.1 nano: 21.8 (#268), MiMo-V2-Pro: 40.8 (#106)
| Benchmark | GPT-4.1 nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1272 | 1479 |
| 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-Pro: —
| Benchmark | GPT-4.1 nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Vision | 1063 | — |
Multilingual MiMo-V2-Pro leads
GPT-4.1 nano: 41.8 (#200), MiMo-V2-Pro: 52.9 (#77)
| Benchmark | GPT-4.1 nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1260 | 1416 |
| LMArena Chinese | 1270 | 1455 |
| LMArena German | 1288 | 1417 |
| LMArena Japanese | 1199 | 1366 |
| LMArena Russian | 1261 | 1427 |
| LMArena French | — | 1470 |
| LMArena Korean | — | 1401 |
| LMArena Spanish | — | 1458 |
Instruction Following MiMo-V2-Pro leads
GPT-4.1 nano: 68.0 (#188), MiMo-V2-Pro: 76.2 (#46)
| Benchmark | GPT-4.1 nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1267 | 1444 |
| IFEval | 84.3% | — |
Long Context MiMo-V2-Pro leads
GPT-4.1 nano: 23.7 (#291), MiMo-V2-Pro: 41.5 (#133)
| Benchmark | GPT-4.1 nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1283 | 1455 |
| Fiction.LiveBench | 25% | — |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |
Writing & Preference MiMo-V2-Pro leads
GPT-4.1 nano: 40.7 (#238), MiMo-V2-Pro: 62.9 (#67)
| Benchmark | GPT-4.1 nano | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1285 | 1436 |
| LMArena Creative Writing | 1260 | 1415 |
| LMArena Multi-Turn | 1277 | 1456 |
| EQ-Bench Creative Writing | 946 | — |
| WildBench | 81.2% | — |
Frequently asked questions
Is GPT-4.1 nano better than MiMo-V2-Pro?
MiMo-V2-Pro is the stronger model overall, scoring 42.4 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-Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 nano or MiMo-V2-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-Pro lists at $0.43 and $0.87.
Is GPT-4.1 nano or MiMo-V2-Pro better for coding?
MiMo-V2-Pro scores higher on coding benchmarks: 43.4 versus 23.8 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Pro does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-4.1 nano and MiMo-V2-Pro share?
14 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and MiMo-V2-Pro has 23.