Noometry

Model comparison

DeepSeek-V3.1 vs MiMo-V2-Omni

DeepSeek-V3.1 and MiMo-V2-Omni score almost the same on the Noometry Index (42.2 vs 42.9), so choose on price, context window or the category you care about most.

Last verified . 17 shared benchmarks.

DeepSeek-V3.1 DeepSeek

42.2

Rank #106 Confirmed

MiMo-V2-Omni Xiaomi

42.9

Rank #91 Confirmed

Summary

  • They share 17 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 1 category and MiMo-V2-Omni in 7 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in long context, where MiMo-V2-Omni leads 44.1 to 36.3.
  • MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.25 / $0.95 for DeepSeek-V3.1.
  • MiMo-V2-Omni accepts more context: 262K tokens versus 164K.
  • DeepSeek-V3.1 has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.1MiMo-V2-Omni
ProviderDeepSeekXiaomi
Noometry Index42.242.9
Released2025-08-212026-03-18
WeightsOpenProprietary
Context window164K262K
Max output8K131K
Input $ / M tokens$0.25$0.14
Output $ / M tokens$0.95$0.28
Results tracked2718

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Category by category

Coding MiMo-V2-Omni leads

DeepSeek-V3.1: 39.8 (#140), MiMo-V2-Omni: 42.7 (#87)

BenchmarkDeepSeek-V3.1MiMo-V2-Omni
LMArena Coding14171467
WeirdML38.4%—

Reasoning MiMo-V2-Omni leads

DeepSeek-V3.1: 27.3 (#109), MiMo-V2-Omni: 28.6 (#86)

BenchmarkDeepSeek-V3.1MiMo-V2-Omni
LMArena Hard Prompts14171445
SimpleBench40%—
Kagi LLM Benchmark53.2%—
DTBench82.7%—
LMCA24.3%—
Epoch Capabilities Index139.92—
ForecastBench58—

Math Too close to call

DeepSeek-V3.1: 36.1 (#125), MiMo-V2-Omni: 36.4 (#112)

BenchmarkDeepSeek-V3.1MiMo-V2-Omni
LMArena Math14201432

Knowledge DeepSeek-V3.1 leads

DeepSeek-V3.1: 43.0 (#86), MiMo-V2-Omni: 39.9 (#114)

BenchmarkDeepSeek-V3.1MiMo-V2-Omni
LMArena Expert14031449
Vectara Hallucination Rate5.5%—

Multimodal Not comparable

DeepSeek-V3.1: —, MiMo-V2-Omni: 37.9 (#62)

BenchmarkDeepSeek-V3.1MiMo-V2-Omni
LMArena Vision—1228

Multilingual Too close to call

DeepSeek-V3.1: 51.8 (#100), MiMo-V2-Omni: 52.0 (#97)

BenchmarkDeepSeek-V3.1MiMo-V2-Omni
LMArena Non-English14001404
LMArena Chinese14701469
LMArena French14471448
LMArena German14121398
LMArena Japanese13741318
LMArena Korean13371355
LMArena Russian14051412
LMArena Spanish14291432

Instruction Following MiMo-V2-Omni leads

DeepSeek-V3.1: 74.1 (#105), MiMo-V2-Omni: 75.4 (#62)

BenchmarkDeepSeek-V3.1MiMo-V2-Omni
LMArena Instruction Following14001428

Long Context MiMo-V2-Omni leads

DeepSeek-V3.1: 36.3 (#227), MiMo-V2-Omni: 44.1 (#72)

BenchmarkDeepSeek-V3.1MiMo-V2-Omni
LMArena Longer Query14221442
Fiction.LiveBench52.8%—

Writing & Preference MiMo-V2-Omni leads

DeepSeek-V3.1: 60.5 (#93), MiMo-V2-Omni: 61.6 (#83)

BenchmarkDeepSeek-V3.1MiMo-V2-Omni
LMArena Text14201424
LMArena Creative Writing14011393
LMArena Multi-Turn14081446
EQ-Bench Creative Writing1436—

Frequently asked questions

Is DeepSeek-V3.1 better than MiMo-V2-Omni?

DeepSeek-V3.1 and MiMo-V2-Omni score almost the same on the Noometry Index (42.2 vs 42.9), so choose on price, context window or the category you care about most.

Which is cheaper, DeepSeek-V3.1 or MiMo-V2-Omni?

MiMo-V2-Omni is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; DeepSeek-V3.1 lists at $0.25 and $0.95.

Is DeepSeek-V3.1 or MiMo-V2-Omni better for coding?

MiMo-V2-Omni scores higher on coding benchmarks: 42.7 versus 39.8 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2-Omni does, with 262K tokens against 164K.

How many benchmarks do DeepSeek-V3.1 and MiMo-V2-Omni share?

17 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and MiMo-V2-Omni has 18.

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