Noometry

Model comparison

MiMo-V2.5 vs Qwen3.8 27B

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 43.4 on the Noometry Index. MiMo-V2.5 costs 3.5× less per token, which makes it the better buy when Qwen3.8 27B's lead doesn't matter for your workload.

Last verified . 22 shared benchmarks.

MiMo-V2.5 Xiaomi

43.4

Rank #93 Confirmed

Qwen3.8 27B Alibaba (Qwen)

46.0

Rank #68 Confirmed

Summary

  • They share 22 benchmarks with published results for both. MiMo-V2.5 scores higher in 0 categories and Qwen3.8 27B in 9 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen3.8 27B leads 41.0 to 28.6.
  • MiMo-V2.5 is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.04 / $2.30 for Qwen3.8 27B.
  • MiMo-V2.5 accepts more context: 1.05M tokens versus 262K.

Side by side

MiMo-V2.5Qwen3.8 27B
ProviderXiaomiAlibaba (Qwen)
Noometry Index43.446.0
Released2026-04-222026-08-14
WeightsOpenOpen
Context window1.05M262K
Max output131K33K
Input $ / M tokens$0.14$0.04
Output $ / M tokens$0.28$2.30
Results tracked2331

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Category by category

Coding Qwen3.8 27B leads

MiMo-V2.5: 43.9 (#81), Qwen3.8 27B: 50.5 (#44)

BenchmarkMiMo-V2.5Qwen3.8 27B
LMArena WebDev14381593
SciCode43.1%46.6%
LMArena Coding14691482
ALE-Bench513.95—

Agentic & Tool Use Not comparable

MiMo-V2.5: —, Qwen3.8 27B: 32.9 (#57)

BenchmarkMiMo-V2.5Qwen3.8 27B
APEX-Agents—47.5%

Reasoning Qwen3.8 27B leads

MiMo-V2.5: 28.6 (#101), Qwen3.8 27B: 41.0 (#54)

BenchmarkMiMo-V2.5Qwen3.8 27B
CritPt3.7%5.4%
LMArena Hard Prompts14501460
ARC-AGI-2—42.4%
NYT Connections (extended)—54.5%
ARC-AGI-1—87.5%
DTBench—88%
LMCA—41.4%
Surface Evolver Bench—45%
Epoch Capabilities Index—149.38

Math Too close to call

MiMo-V2.5: 36.8 (#163), Qwen3.8 27B: 37.1 (#161)

BenchmarkMiMo-V2.5Qwen3.8 27B
ProofBench16%16%
LMArena Math14361456

Knowledge Too close to call

MiMo-V2.5: 40.8 (#115), Qwen3.8 27B: 41.6 (#109)

BenchmarkMiMo-V2.5Qwen3.8 27B
LMArena Expert14601482

Multimodal Qwen3.8 27B leads

MiMo-V2.5: 39.8 (#54), Qwen3.8 27B: 41.3 (#37)

BenchmarkMiMo-V2.5Qwen3.8 27B
LMArena Vision12471271

Multilingual Qwen3.8 27B leads

MiMo-V2.5: 51.9 (#99), Qwen3.8 27B: 53.7 (#60)

BenchmarkMiMo-V2.5Qwen3.8 27B
LMArena Non-English14041430
LMArena Chinese14681504
LMArena French14471465
LMArena German14211438
LMArena Japanese13061384
LMArena Korean13631393
LMArena Russian13951415
LMArena Spanish14161448

Instruction Following Too close to call

MiMo-V2.5: 75.5 (#60), Qwen3.8 27B: 75.8 (#53)

BenchmarkMiMo-V2.5Qwen3.8 27B
LMArena Instruction Following14341439

Long Context Too close to call

MiMo-V2.5: 44.2 (#73), Qwen3.8 27B: 44.3 (#70)

BenchmarkMiMo-V2.5Qwen3.8 27B
LMArena Longer Query14451450

Writing & Preference Qwen3.8 27B leads

MiMo-V2.5: 61.6 (#86), Qwen3.8 27B: 65.8 (#43)

BenchmarkMiMo-V2.5Qwen3.8 27B
LMArena Text14281441
LMArena Creative Writing13931384
LMArena Multi-Turn14451441
EQ-Bench Creative Writing—1671

Frequently asked questions

Is MiMo-V2.5 better than Qwen3.8 27B?

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 43.4 on the Noometry Index. MiMo-V2.5 costs 3.5× 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-V2.5 or Qwen3.8 27B?

MiMo-V2.5 is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; Qwen3.8 27B lists at $0.04 and $2.30.

Is MiMo-V2.5 or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.5 versus 43.9 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2.5 does, with 1.05M tokens against 262K.

How many benchmarks do MiMo-V2.5 and Qwen3.8 27B share?

22 benchmarks have published results for both models. MiMo-V2.5 has 23 scored results on Noometry and Qwen3.8 27B has 31.

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