Model comparison

DeepSeek-V3.1 vs MiMo-V2.6-Flash

MiMo-V2.6-Flash is the stronger model overall, scoring 44.4 to 42.2 on the Noometry Index.

Last verified . 12 shared benchmarks.

DeepSeek-V3.1 DeepSeek

42.2

Rank #106 Confirmed

MiMo-V2.6-Flash Xiaomi

44.4

Rank #74 Confirmed

Summary

  • They share 12 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 1 category and MiMo-V2.6-Flash in 7 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in long context, where MiMo-V2.6-Flash leads 44.8 to 36.3.
  • MiMo-V2.6-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.25 / $0.95 for DeepSeek-V3.1.
  • MiMo-V2.6-Flash accepts more context: 1.05M tokens versus 164K.

Side by side

DeepSeek-V3.1 and MiMo-V2.6-Flash specifications
DeepSeek-V3.1MiMo-V2.6-Flash
ProviderDeepSeekXiaomi
Noometry Index42.244.4
Released2025-08-212026-09-22
WeightsOpenOpen
Context window164K1.05M
Max output8K131K
Input $ / M tokens$0.25$0.14
Output $ / M tokens$0.95$0.28
Results tracked2713

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding MiMo-V2.6-Flash leads

DeepSeek-V3.1: 39.8 (#140), MiMo-V2.6-Flash: 44.3 (#68)

Coding benchmarks
BenchmarkDeepSeek-V3.1MiMo-V2.6-Flash
LMArena Coding14171516
WeirdML38.4%—

Reasoning MiMo-V2.6-Flash leads

DeepSeek-V3.1: 27.3 (#109), MiMo-V2.6-Flash: 29.6 (#82)

Reasoning benchmarks
BenchmarkDeepSeek-V3.1MiMo-V2.6-Flash
LMArena Hard Prompts14171481
SimpleBench40%—
Kagi LLM Benchmark53.2%—
DTBench82.7%—
LMCA24.3%—
Epoch Capabilities Index139.92—
ForecastBench58—

Math MiMo-V2.6-Flash leads

DeepSeek-V3.1: 36.1 (#125), MiMo-V2.6-Flash: 37.4 (#97)

Math benchmarks
BenchmarkDeepSeek-V3.1MiMo-V2.6-Flash
LMArena Math14201477

Knowledge DeepSeek-V3.1 leads

DeepSeek-V3.1: 43.0 (#86), MiMo-V2.6-Flash: 42.0 (#91)

Knowledge benchmarks
BenchmarkDeepSeek-V3.1MiMo-V2.6-Flash
LMArena Expert14031516
Vectara Hallucination Rate5.5%—

Multimodal Not comparable

DeepSeek-V3.1: —, MiMo-V2.6-Flash: 40.2 (#39)

Multimodal benchmarks
BenchmarkDeepSeek-V3.1MiMo-V2.6-Flash
LMArena Vision—1266

Multilingual MiMo-V2.6-Flash leads

DeepSeek-V3.1: 51.8 (#100), MiMo-V2.6-Flash: 54.6 (#41)

Multilingual benchmarks
BenchmarkDeepSeek-V3.1MiMo-V2.6-Flash
LMArena Non-English14001439
LMArena Chinese14701501
LMArena Russian14051424
LMArena French1447—
LMArena German1412—
LMArena Japanese1374—
LMArena Korean1337—
LMArena Spanish1429—

Instruction Following MiMo-V2.6-Flash leads

DeepSeek-V3.1: 74.1 (#105), MiMo-V2.6-Flash: 77.0 (#33)

Instruction Following benchmarks
BenchmarkDeepSeek-V3.1MiMo-V2.6-Flash
LMArena Instruction Following14001463

Long Context MiMo-V2.6-Flash leads

DeepSeek-V3.1: 36.3 (#227), MiMo-V2.6-Flash: 44.8 (#52)

Long Context benchmarks
BenchmarkDeepSeek-V3.1MiMo-V2.6-Flash
LMArena Longer Query14221465
Fiction.LiveBench52.8%—

Writing & Preference MiMo-V2.6-Flash leads

DeepSeek-V3.1: 60.5 (#93), MiMo-V2.6-Flash: 63.9 (#61)

Writing & Preference benchmarks
BenchmarkDeepSeek-V3.1MiMo-V2.6-Flash
LMArena Text14201459
LMArena Creative Writing14011408
LMArena Multi-Turn14081460
EQ-Bench Creative Writing1436—

Frequently asked questions

Is DeepSeek-V3.1 better than MiMo-V2.6-Flash?

MiMo-V2.6-Flash is the stronger model overall, scoring 44.4 to 42.2 on the Noometry Index.

Which is cheaper, DeepSeek-V3.1 or MiMo-V2.6-Flash?

MiMo-V2.6-Flash 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-V2.6-Flash better for coding?

MiMo-V2.6-Flash scores higher on coding benchmarks: 44.3 versus 39.8 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2.6-Flash does, with 1.05M tokens against 164K.

How many benchmarks do DeepSeek-V3.1 and MiMo-V2.6-Flash share?

12 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and MiMo-V2.6-Flash has 13.

Related comparisons

Go deeper