Noometry

Model comparison

MiMo-V2-Flash vs Qwen3-30B-A3B

MiMo-V2-Flash is the stronger model overall, scoring 40.8 to 38.5 on the Noometry Index.

Last verified . 19 shared benchmarks.

MiMo-V2-Flash Xiaomi

40.8

Rank #137 Confirmed

Qwen3-30B-A3B Alibaba (Qwen)

38.5

Rank #174 Confirmed

Summary

  • They share 19 benchmarks with published results for both. MiMo-V2-Flash scores higher in 5 categories and Qwen3-30B-A3B in 3 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in long context, where MiMo-V2-Flash leads 43.0 to 31.0.
  • The biggest single-benchmark swing is SciCode: 25.9% for MiMo-V2-Flash and 33.3% for Qwen3-30B-A3B.
  • MiMo-V2-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.12 / $0.50 for Qwen3-30B-A3B.
  • MiMo-V2-Flash accepts more context: 262K tokens versus 41K.

Side by side

MiMo-V2-FlashQwen3-30B-A3B
ProviderXiaomiAlibaba (Qwen)
Noometry Index40.838.5
Released2025-12-162025-04-28
WeightsOpenOpen
Context window262K41K
Max output66K16K
Input $ / M tokens$0.14$0.12
Output $ / M tokens$0.28$0.50
Results tracked2132

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Category by category

Coding Qwen3-30B-A3B leads

MiMo-V2-Flash: 35.8 (#205), Qwen3-30B-A3B: 37.0 (#188)

BenchmarkMiMo-V2-FlashQwen3-30B-A3B
SciCode25.9%33.3%
LMArena Coding14431416
LMArena WebDev1330—
WeirdML—29.8%
ALE-Bench737.95—

Agentic & Tool Use Not comparable

MiMo-V2-Flash: —, Qwen3-30B-A3B: 29.5 (#75)

BenchmarkMiMo-V2-FlashQwen3-30B-A3B
Berkeley Function Calling Leaderboard—41.4%

Reasoning MiMo-V2-Flash leads

MiMo-V2-Flash: 24.1 (#155), Qwen3-30B-A3B: 21.6 (#193)

BenchmarkMiMo-V2-FlashQwen3-30B-A3B
CritPt0%0.3%
LMArena Hard Prompts14201398
Kagi LLM Benchmark—54.9%
Chess Puzzles—8%
DTBench—69.3%
LMCA—22.4%
Epoch Capabilities Index—139.63

Math Too close to call

MiMo-V2-Flash: 35.6 (#141), Qwen3-30B-A3B: 36.0 (#133)

BenchmarkMiMo-V2-FlashQwen3-30B-A3B
LMArena Math13961394
MathArena Final-Answer Competitions—47.8%
OTIS Mock AIME 2024-2025—70.3%

Knowledge Qwen3-30B-A3B leads

MiMo-V2-Flash: 39.1 (#126), Qwen3-30B-A3B: 41.7 (#96)

BenchmarkMiMo-V2-FlashQwen3-30B-A3B
LMArena Expert14251395
GPQA Diamond—70.1%
Confabulations—12.3%

Multilingual MiMo-V2-Flash leads

MiMo-V2-Flash: 51.1 (#109), Qwen3-30B-A3B: 49.8 (#126)

BenchmarkMiMo-V2-FlashQwen3-30B-A3B
LMArena Non-English13911372
LMArena Chinese14631434
LMArena French14291419
LMArena German13951379
LMArena Japanese13241338
LMArena Korean13581333
LMArena Russian13871369
LMArena Spanish14201403

Instruction Following MiMo-V2-Flash leads

MiMo-V2-Flash: 73.7 (#115), Qwen3-30B-A3B: 72.2 (#137)

BenchmarkMiMo-V2-FlashQwen3-30B-A3B
LMArena Instruction Following13921364

Long Context MiMo-V2-Flash leads

MiMo-V2-Flash: 43.0 (#106), Qwen3-30B-A3B: 31.0 (#278)

BenchmarkMiMo-V2-FlashQwen3-30B-A3B
LMArena Longer Query14091379
Fiction.LiveBench—40.6%

Writing & Preference MiMo-V2-Flash leads

MiMo-V2-Flash: 59.9 (#101), Qwen3-30B-A3B: 55.9 (#138)

BenchmarkMiMo-V2-FlashQwen3-30B-A3B
LMArena Text14111384
LMArena Creative Writing13751318
LMArena Multi-Turn14041378
Short-Story Creative Writing—75.3%

Frequently asked questions

Is MiMo-V2-Flash better than Qwen3-30B-A3B?

MiMo-V2-Flash is the stronger model overall, scoring 40.8 to 38.5 on the Noometry Index.

Which is cheaper, MiMo-V2-Flash or Qwen3-30B-A3B?

MiMo-V2-Flash is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; Qwen3-30B-A3B lists at $0.12 and $0.50.

Is MiMo-V2-Flash or Qwen3-30B-A3B better for coding?

Qwen3-30B-A3B scores higher on coding benchmarks: 37.0 versus 35.8 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2-Flash does, with 262K tokens against 41K.

How many benchmarks do MiMo-V2-Flash and Qwen3-30B-A3B share?

19 benchmarks have published results for both models. MiMo-V2-Flash has 21 scored results on Noometry and Qwen3-30B-A3B has 32.

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