Model comparison
MiMo-V2-Flash vs Trinity Large Thinking
MiMo-V2-Flash is the stronger model overall, scoring 41.3 to 38.6 on the Noometry Index.
Last verified . 20 shared benchmarks.
Arcee AISummary
- They share 20 benchmarks with published results for both. MiMo-V2-Flash scores higher in 7 categories and Trinity Large Thinking in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where MiMo-V2-Flash leads 24.9 to 16.9.
- The biggest single-benchmark swing is SciCode: 25.9% for MiMo-V2-Flash and 36.1% for Trinity Large Thinking.
- MiMo-V2-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.25 / $0.80 for Trinity Large Thinking.
Side by side
| MiMo-V2-Flash | Trinity Large Thinking | |
|---|---|---|
| Provider | Xiaomi | Arcee AI |
| Noometry Index | 41.3 | 38.6 |
| Released | 2025-12-16 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 66K | 80K |
| Input $ / M tokens | $0.14 | $0.25 |
| Output $ / M tokens | $0.28 | $0.80 |
| Results tracked | 21 | 24 |
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Category by category
Coding MiMo-V2-Flash leads
MiMo-V2-Flash: 36.1 (#211), Trinity Large Thinking: 34.1 (#244)
| Benchmark | MiMo-V2-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | 1330 | 1238 |
| SciCode | 25.9% | 36.1% |
| LMArena Coding | 1443 | 1381 |
| ALE-Bench | 737.95 | — |
Reasoning MiMo-V2-Flash leads
MiMo-V2-Flash: 24.9 (#157), Trinity Large Thinking: 16.9 (#298)
| Benchmark | MiMo-V2-Flash | Trinity Large Thinking |
|---|---|---|
| CritPt | 0% | 0.9% |
| LMArena Hard Prompts | 1420 | 1350 |
| NYT Connections (extended) | — | 16.5% |
| Thematic Generalization | — | 41.6% |
| Surface Evolver Bench | — | 15.6% |
Math Too close to call
MiMo-V2-Flash: 38.3 (#139), Trinity Large Thinking: 37.6 (#149)
| Benchmark | MiMo-V2-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1396 | 1366 |
Knowledge Trinity Large Thinking leads
MiMo-V2-Flash: 39.7 (#131), Trinity Large Thinking: 40.9 (#113)
| Benchmark | MiMo-V2-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1425 | 1360 |
| Vectara Hallucination Rate | — | 6.9% |
Multilingual MiMo-V2-Flash leads
MiMo-V2-Flash: 51.0 (#113), Trinity Large Thinking: 46.2 (#160)
| Benchmark | MiMo-V2-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1392 | 1325 |
| LMArena Chinese | 1462 | 1373 |
| LMArena French | 1429 | 1374 |
| LMArena German | 1395 | 1356 |
| LMArena Japanese | 1325 | 1311 |
| LMArena Korean | 1358 | 1306 |
| LMArena Russian | 1387 | 1337 |
| LMArena Spanish | 1420 | 1357 |
Instruction Following MiMo-V2-Flash leads
MiMo-V2-Flash: 73.5 (#120), Trinity Large Thinking: 70.5 (#162)
| Benchmark | MiMo-V2-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1392 | 1334 |
Long Context MiMo-V2-Flash leads
MiMo-V2-Flash: 43.0 (#110), Trinity Large Thinking: 41.3 (#144)
| Benchmark | MiMo-V2-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1409 | 1355 |
Writing & Preference MiMo-V2-Flash leads
MiMo-V2-Flash: 59.7 (#106), Trinity Large Thinking: 53.8 (#158)
| Benchmark | MiMo-V2-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1411 | 1340 |
| LMArena Creative Writing | 1375 | 1320 |
| LMArena Multi-Turn | 1404 | 1342 |
Frequently asked questions
Is MiMo-V2-Flash better than Trinity Large Thinking?
MiMo-V2-Flash is the stronger model overall, scoring 41.3 to 38.6 on the Noometry Index.
Which is cheaper, MiMo-V2-Flash or Trinity Large Thinking?
MiMo-V2-Flash is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; Trinity Large Thinking lists at $0.25 and $0.80.
Is MiMo-V2-Flash or Trinity Large Thinking better for coding?
MiMo-V2-Flash scores higher on coding benchmarks: 36.1 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do MiMo-V2-Flash and Trinity Large Thinking share?
20 benchmarks have published results for both models. MiMo-V2-Flash has 21 scored results on Noometry and Trinity Large Thinking has 24.