Noometry

Model comparison

MiMo-V2-Flash vs Qwen3.8 27B

Qwen3.8 27B is the stronger model overall, scoring 45.3 to 40.8 on the Noometry Index. MiMo-V2-Flash costs 6.4× less per token, which makes it the better buy when Qwen3.8 27B's lead doesn't matter for your workload.

Last verified . 20 shared benchmarks.

MiMo-V2-Flash Xiaomi

40.8

Rank #137 Confirmed

Qwen3.8 27B Alibaba (Qwen)

45.3

Rank #64 Confirmed

Summary

  • They share 20 benchmarks with published results for both. MiMo-V2-Flash scores higher in 0 categories and Qwen3.8 27B in 8 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in coding, where Qwen3.8 27B leads 50.3 to 35.8.
  • The biggest single-benchmark swing is SciCode: 25.9% for MiMo-V2-Flash and 46.6% for Qwen3.8 27B.
  • MiMo-V2-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.99 / $1.49 for Qwen3.8 27B.

Side by side

MiMo-V2-FlashQwen3.8 27B
ProviderXiaomiAlibaba (Qwen)
Noometry Index40.845.3
Released2025-12-162026-08-14
WeightsOpenOpen
Context window262K262K
Max output66K33K
Input $ / M tokens$0.14$0.99
Output $ / M tokens$0.28$1.49
Results tracked2128

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Category by category

Coding Qwen3.8 27B leads

MiMo-V2-Flash: 35.8 (#205), Qwen3.8 27B: 50.3 (#42)

BenchmarkMiMo-V2-FlashQwen3.8 27B
LMArena WebDev13301592
SciCode25.9%46.6%
LMArena Coding14431487
ALE-Bench737.95—

Reasoning Qwen3.8 27B leads

MiMo-V2-Flash: 24.1 (#155), Qwen3.8 27B: 31.5 (#71)

BenchmarkMiMo-V2-FlashQwen3.8 27B
CritPt0%5.4%
LMArena Hard Prompts14201459
NYT Connections (extended)—54.5%
DTBench—88%
LMCA—41.4%
Surface Evolver Bench—45%
Epoch Capabilities Index—149.38

Math Too close to call

MiMo-V2-Flash: 35.6 (#141), Qwen3.8 27B: 35.7 (#139)

BenchmarkMiMo-V2-FlashQwen3.8 27B
LMArena Math13961453
ProofBench—16%

Knowledge Qwen3.8 27B leads

MiMo-V2-Flash: 39.1 (#126), Qwen3.8 27B: 40.9 (#105)

BenchmarkMiMo-V2-FlashQwen3.8 27B
LMArena Expert14251482

Multimodal Not comparable

MiMo-V2-Flash: —, Qwen3.8 27B: 40.5 (#36)

BenchmarkMiMo-V2-FlashQwen3.8 27B
LMArena Vision—1270

Multilingual Qwen3.8 27B leads

MiMo-V2-Flash: 51.1 (#109), Qwen3.8 27B: 54.0 (#54)

BenchmarkMiMo-V2-FlashQwen3.8 27B
LMArena Non-English13911431
LMArena Chinese14631504
LMArena French14291468
LMArena German13951435
LMArena Japanese13241392
LMArena Korean13581389
LMArena Russian13871421
LMArena Spanish14201444

Instruction Following Qwen3.8 27B leads

MiMo-V2-Flash: 73.7 (#115), Qwen3.8 27B: 75.8 (#54)

BenchmarkMiMo-V2-FlashQwen3.8 27B
LMArena Instruction Following13921436

Long Context Qwen3.8 27B leads

MiMo-V2-Flash: 43.0 (#106), Qwen3.8 27B: 44.3 (#66)

BenchmarkMiMo-V2-FlashQwen3.8 27B
LMArena Longer Query14091448

Writing & Preference Qwen3.8 27B leads

MiMo-V2-Flash: 59.9 (#101), Qwen3.8 27B: 65.9 (#41)

BenchmarkMiMo-V2-FlashQwen3.8 27B
LMArena Text14111441
LMArena Creative Writing13751382
LMArena Multi-Turn14041443
EQ-Bench Creative Writing—1671

Frequently asked questions

Is MiMo-V2-Flash better than Qwen3.8 27B?

Qwen3.8 27B is the stronger model overall, scoring 45.3 to 40.8 on the Noometry Index. MiMo-V2-Flash costs 6.4× less per token, which makes it the better buy when Qwen3.8 27B's lead doesn't matter for your workload.

Which is cheaper, MiMo-V2-Flash or Qwen3.8 27B?

MiMo-V2-Flash is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; Qwen3.8 27B lists at $0.99 and $1.49.

Is MiMo-V2-Flash or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.3 versus 35.8 in the Noometry coding category.

Which has the bigger context window?

Both accept 262K tokens.

How many benchmarks do MiMo-V2-Flash and Qwen3.8 27B share?

20 benchmarks have published results for both models. MiMo-V2-Flash has 21 scored results on Noometry and Qwen3.8 27B has 28.

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