Noometry

Model comparison

DeepSeek-V3.1-Terminus vs MiMo-V2-Omni

DeepSeek-V3.1-Terminus and MiMo-V2-Omni score almost the same on the Noometry Index (43.1 vs 43.6), so choose on price, context window or the category you care about most.

Last verified . 10 shared benchmarks.

DeepSeek-V3.1-Terminus DeepSeek

43.1

Rank #97 Confirmed

MiMo-V2-Omni Xiaomi

43.6

Rank #88 Confirmed

Summary

  • They share 10 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 1 category and MiMo-V2-Omni in 6 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where MiMo-V2-Omni leads 29.7 to 26.4.
  • MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.27 / $1 for DeepSeek-V3.1-Terminus.
  • MiMo-V2-Omni accepts more context: 262K tokens versus 164K.
  • DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.1-TerminusMiMo-V2-Omni
ProviderDeepSeekXiaomi
Noometry Index43.143.6
Released2025-09-222026-03-18
WeightsOpenProprietary
Context window164K262K
Max output147K131K
Input $ / M tokens$0.27$0.14
Output $ / M tokens$1$0.28
Results tracked1618

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

Category by category

Coding MiMo-V2-Omni leads

DeepSeek-V3.1-Terminus: 42.0 (#113), MiMo-V2-Omni: 43.3 (#89)

BenchmarkDeepSeek-V3.1-TerminusMiMo-V2-Omni
LMArena Coding14261466
SciCode40.6%—
ALE-Bench745.17—

Reasoning MiMo-V2-Omni leads

DeepSeek-V3.1-Terminus: 26.4 (#133), MiMo-V2-Omni: 29.7 (#88)

BenchmarkDeepSeek-V3.1-TerminusMiMo-V2-Omni
LMArena Hard Prompts14261445
Kagi LLM Benchmark57.4%—
CritPt1.7%—
DTBench81.3%—
LMCA28.6%—

Math Too close to call

DeepSeek-V3.1-Terminus: 38.5 (#137), MiMo-V2-Omni: 39.1 (#115)

BenchmarkDeepSeek-V3.1-TerminusMiMo-V2-Omni
LMArena Math14021430

Knowledge Not comparable

DeepSeek-V3.1-Terminus: —, MiMo-V2-Omni: 40.5 (#118)

BenchmarkDeepSeek-V3.1-TerminusMiMo-V2-Omni
LMArena Expert—1449

Multimodal Not comparable

DeepSeek-V3.1-Terminus: —, MiMo-V2-Omni: 38.6 (#63)

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

Multilingual Too close to call

DeepSeek-V3.1-Terminus: 52.1 (#92), MiMo-V2-Omni: 51.8 (#102)

BenchmarkDeepSeek-V3.1-TerminusMiMo-V2-Omni
LMArena Non-English14071404
LMArena Russian14361412
LMArena Chinese—1465
LMArena French—1447
LMArena German—1399
LMArena Japanese—1317
LMArena Korean—1355
LMArena Spanish—1434

Instruction Following MiMo-V2-Omni leads

DeepSeek-V3.1-Terminus: 74.0 (#106), MiMo-V2-Omni: 75.2 (#66)

BenchmarkDeepSeek-V3.1-TerminusMiMo-V2-Omni
LMArena Instruction Following14041428

Long Context Too close to call

DeepSeek-V3.1-Terminus: 43.4 (#97), MiMo-V2-Omni: 44.1 (#76)

BenchmarkDeepSeek-V3.1-TerminusMiMo-V2-Omni
LMArena Longer Query14211442

Writing & Preference Too close to call

DeepSeek-V3.1-Terminus: 61.0 (#92), MiMo-V2-Omni: 61.4 (#87)

BenchmarkDeepSeek-V3.1-TerminusMiMo-V2-Omni
LMArena Text14191423
LMArena Creative Writing14031392
LMArena Multi-Turn14111445

Frequently asked questions

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

DeepSeek-V3.1-Terminus and MiMo-V2-Omni score almost the same on the Noometry Index (43.1 vs 43.6), so choose on price, context window or the category you care about most.

Which is cheaper, DeepSeek-V3.1-Terminus 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-Terminus lists at $0.27 and $1.

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

MiMo-V2-Omni scores higher on coding benchmarks: 43.3 versus 42.0 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-Terminus and MiMo-V2-Omni share?

10 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and MiMo-V2-Omni has 18.

Related comparisons

Go deeper