Noometry

Model comparison

MiMo-V2-Omni vs Qwen3.8 27B

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 43.6 on the Noometry Index. MiMo-V2-Omni 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 . 18 shared benchmarks.

MiMo-V2-Omni Xiaomi

43.6

Rank #88 Confirmed

Qwen3.8 27B Alibaba (Qwen)

46.0

Rank #68 Confirmed

Summary

  • They share 18 benchmarks with published results for both. MiMo-V2-Omni scores higher in 1 category and Qwen3.8 27B in 8 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen3.8 27B leads 41.0 to 29.7.
  • MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.99 / $1.49 for Qwen3.8 27B.
  • Qwen3.8 27B has downloadable open weights; the other is API-only.

Side by side

MiMo-V2-OmniQwen3.8 27B
ProviderXiaomiAlibaba (Qwen)
Noometry Index43.646.0
Released2026-03-182026-08-14
WeightsProprietaryOpen
Context window262K262K
Max output131K33K
Input $ / M tokens$0.14$0.99
Output $ / M tokens$0.28$1.49
Results tracked1831

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Category by category

Coding Qwen3.8 27B leads

MiMo-V2-Omni: 43.3 (#89), Qwen3.8 27B: 50.5 (#44)

BenchmarkMiMo-V2-OmniQwen3.8 27B
LMArena Coding14661482
LMArena WebDev—1593
SciCode—46.6%

Agentic & Tool Use Not comparable

MiMo-V2-Omni: —, Qwen3.8 27B: 32.9 (#57)

BenchmarkMiMo-V2-OmniQwen3.8 27B
APEX-Agents—47.5%

Reasoning Qwen3.8 27B leads

MiMo-V2-Omni: 29.7 (#88), Qwen3.8 27B: 41.0 (#54)

BenchmarkMiMo-V2-OmniQwen3.8 27B
LMArena Hard Prompts14451460
ARC-AGI-2—42.4%
NYT Connections (extended)—54.5%
ARC-AGI-1—87.5%
CritPt—5.4%
DTBench—88%
LMCA—41.4%
Surface Evolver Bench—45%
Epoch Capabilities Index—149.38

Math MiMo-V2-Omni leads

MiMo-V2-Omni: 39.1 (#115), Qwen3.8 27B: 37.1 (#161)

BenchmarkMiMo-V2-OmniQwen3.8 27B
LMArena Math14301456
ProofBench—16%

Knowledge Qwen3.8 27B leads

MiMo-V2-Omni: 40.5 (#118), Qwen3.8 27B: 41.6 (#109)

BenchmarkMiMo-V2-OmniQwen3.8 27B
LMArena Expert14491482

Multimodal Qwen3.8 27B leads

MiMo-V2-Omni: 38.6 (#63), Qwen3.8 27B: 41.3 (#37)

BenchmarkMiMo-V2-OmniQwen3.8 27B
LMArena Vision12281271

Multilingual Qwen3.8 27B leads

MiMo-V2-Omni: 51.8 (#102), Qwen3.8 27B: 53.7 (#60)

BenchmarkMiMo-V2-OmniQwen3.8 27B
LMArena Non-English14041430
LMArena Chinese14651504
LMArena French14471465
LMArena German13991438
LMArena Japanese13171384
LMArena Korean13551393
LMArena Russian14121415
LMArena Spanish14341448

Instruction Following Too close to call

MiMo-V2-Omni: 75.2 (#66), Qwen3.8 27B: 75.8 (#53)

BenchmarkMiMo-V2-OmniQwen3.8 27B
LMArena Instruction Following14281439

Long Context Too close to call

MiMo-V2-Omni: 44.1 (#76), Qwen3.8 27B: 44.3 (#70)

BenchmarkMiMo-V2-OmniQwen3.8 27B
LMArena Longer Query14421450

Writing & Preference Qwen3.8 27B leads

MiMo-V2-Omni: 61.4 (#87), Qwen3.8 27B: 65.8 (#43)

BenchmarkMiMo-V2-OmniQwen3.8 27B
LMArena Text14231441
LMArena Creative Writing13921384
LMArena Multi-Turn14451441
EQ-Bench Creative Writing—1671

Frequently asked questions

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

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 43.6 on the Noometry Index. MiMo-V2-Omni 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-Omni or Qwen3.8 27B?

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

Qwen3.8 27B scores higher on coding benchmarks: 50.5 versus 43.3 in the Noometry coding category.

Which has the bigger context window?

Both accept 262K tokens.

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

18 benchmarks have published results for both models. MiMo-V2-Omni has 18 scored results on Noometry and Qwen3.8 27B has 31.

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