Model comparison
GPT-4.1 mini vs MiMo-V2.6-Flash
MiMo-V2.6-Flash is the stronger model overall, scoring 44.4 to 33.5 on the Noometry Index.
Last verified . 13 shared benchmarks.
Summary
- They share 13 benchmarks with published results for both. GPT-4.1 mini scores higher in 0 categories and MiMo-V2.6-Flash in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where MiMo-V2.6-Flash leads 29.6 to 10.9.
- MiMo-V2.6-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.40 / $1.60 for GPT-4.1 mini.
- MiMo-V2.6-Flash accepts more context: 1.05M tokens versus 1.05M.
- MiMo-V2.6-Flash has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 mini | MiMo-V2.6-Flash | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 33.5 | 44.4 |
| Released | 2025-04-14 | 2026-09-22 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 1.05M |
| Max output | 33K | 131K |
| Input $ / M tokens | $0.40 | $0.14 |
| Output $ / M tokens | $1.60 | $0.28 |
| Results tracked | 47 | 13 |
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Category by category
Coding MiMo-V2.6-Flash leads
GPT-4.1 mini: 30.4 (#286), MiMo-V2.6-Flash: 44.3 (#68)
| Benchmark | GPT-4.1 mini | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Coding | 1367 | 1516 |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| SciCode | 40.4% | — |
| WeirdML | 37.6% | — |
| BigCodeBench Instruct | 48.9% | — |
| CadEval | 16% | — |
Agentic & Tool Use Not comparable
GPT-4.1 mini: 33.0 (#52), MiMo-V2.6-Flash: —
| Benchmark | GPT-4.1 mini | MiMo-V2.6-Flash |
|---|---|---|
| Berkeley Function Calling Leaderboard | 50.5% | — |
Reasoning MiMo-V2.6-Flash leads
GPT-4.1 mini: 10.9 (#335), MiMo-V2.6-Flash: 29.6 (#82)
| Benchmark | GPT-4.1 mini | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Hard Prompts | 1349 | 1481 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 48.6% | — |
| ARC-AGI-1 | 3.5% | — |
| CritPt | 0% | — |
| Chess Puzzles | 7% | — |
| Mystery Game Puzzles | 7% | — |
| DTBench | 68.8% | — |
| LMCA | 21.1% | — |
| Epoch Capabilities Index | 135.01 | — |
Math MiMo-V2.6-Flash leads
GPT-4.1 mini: 23.1 (#264), MiMo-V2.6-Flash: 37.4 (#97)
| Benchmark | GPT-4.1 mini | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Math | 1343 | 1477 |
| FrontierMath (Tiers 1-3) | 6.7% | — |
| OTIS Mock AIME 2024-2025 | 44.7% | — |
| Omni-MATH | 49.1% | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
Knowledge MiMo-V2.6-Flash leads
GPT-4.1 mini: 34.7 (#183), MiMo-V2.6-Flash: 42.0 (#91)
| Benchmark | GPT-4.1 mini | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Expert | 1338 | 1516 |
| GPQA Diamond | 65.8% | — |
| SimpleQA Verified | 12.7% | — |
| MMLU-Pro | 78.3% | — |
| GPQA (HELM) | 61.4% | — |
Multimodal MiMo-V2.6-Flash leads
GPT-4.1 mini: 35.2 (#77), MiMo-V2.6-Flash: 40.2 (#39)
| Benchmark | GPT-4.1 mini | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Vision | 1181 | 1266 |
Multilingual MiMo-V2.6-Flash leads
GPT-4.1 mini: 45.9 (#161), MiMo-V2.6-Flash: 54.6 (#41)
| Benchmark | GPT-4.1 mini | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Non-English | 1318 | 1439 |
| LMArena Chinese | 1329 | 1501 |
| LMArena Russian | 1324 | 1424 |
| LMArena French | 1357 | — |
| LMArena German | 1349 | — |
| LMArena Japanese | 1291 | — |
| LMArena Korean | 1298 | — |
| LMArena Spanish | 1319 | — |
Instruction Following MiMo-V2.6-Flash leads
GPT-4.1 mini: 73.9 (#113), MiMo-V2.6-Flash: 77.0 (#33)
| Benchmark | GPT-4.1 mini | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Instruction Following | 1332 | 1463 |
| IFEval | 90.4% | — |
Long Context MiMo-V2.6-Flash leads
GPT-4.1 mini: 31.8 (#270), MiMo-V2.6-Flash: 44.8 (#52)
| Benchmark | GPT-4.1 mini | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Longer Query | 1344 | 1465 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference MiMo-V2.6-Flash leads
GPT-4.1 mini: 48.8 (#193), MiMo-V2.6-Flash: 63.9 (#61)
| Benchmark | GPT-4.1 mini | MiMo-V2.6-Flash |
|---|---|---|
| LMArena Text | 1341 | 1459 |
| LMArena Creative Writing | 1300 | 1408 |
| LMArena Multi-Turn | 1354 | 1460 |
| EQ-Bench Creative Writing | 1147 | — |
| WildBench | 83.8% | — |
Frequently asked questions
Is GPT-4.1 mini better than MiMo-V2.6-Flash?
MiMo-V2.6-Flash is the stronger model overall, scoring 44.4 to 33.5 on the Noometry Index.
Which is cheaper, GPT-4.1 mini or MiMo-V2.6-Flash?
MiMo-V2.6-Flash is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; GPT-4.1 mini lists at $0.40 and $1.60.
Is GPT-4.1 mini or MiMo-V2.6-Flash better for coding?
MiMo-V2.6-Flash scores higher on coding benchmarks: 44.3 versus 30.4 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.6-Flash does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-4.1 mini and MiMo-V2.6-Flash share?
13 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and MiMo-V2.6-Flash has 13.