Model comparison

DeepSeek-V3.1-Terminus vs MiMo-V2.5

DeepSeek-V3.1-Terminus and MiMo-V2.5 score almost the same on the Noometry Index (42.6 vs 43.0), so choose on price, context window or the category you care about most.

Last verified . 13 shared benchmarks.

DeepSeek-V3.1-Terminus DeepSeek

42.6

Rank #96 Confirmed

MiMo-V2.5 Xiaomi

43.0

Rank #89 Confirmed

Summary

  • They share 13 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 2 categories and MiMo-V2.5 in 5 categories; 3 gaps are clear of the uncertainty.
  • MiMo-V2.5 is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.30 / $1 for DeepSeek-V3.1-Terminus.
  • MiMo-V2.5 accepts more context: 1.05M tokens versus 164K.

Side by side

DeepSeek-V3.1-Terminus and MiMo-V2.5 specifications
DeepSeek-V3.1-TerminusMiMo-V2.5
ProviderDeepSeekXiaomi
Noometry Index42.643.0
Released2025-09-222026-04-22
WeightsOpenOpen
Context window164K1.05M
Max output66K131K
Input $ / M tokens$0.30$0.14
Output $ / M tokens$1$0.28
Results tracked1623

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Category by category

Coding MiMo-V2.5 leads

DeepSeek-V3.1-Terminus: 41.5 (#114), MiMo-V2.5: 43.6 (#75)

Coding benchmarks
BenchmarkDeepSeek-V3.1-TerminusMiMo-V2.5
SciCode40.6%43.1%
LMArena Coding14261469
ALE-Bench745.17513.95
LMArena WebDev—1438

Reasoning MiMo-V2.5 leads

DeepSeek-V3.1-Terminus: 25.7 (#126), MiMo-V2.5: 27.8 (#98)

Reasoning benchmarks
BenchmarkDeepSeek-V3.1-TerminusMiMo-V2.5
CritPt1.7%3.7%
LMArena Hard Prompts14271450
Kagi LLM Benchmark57.4%—
DTBench81.3%—
LMCA28.6%—

Math Too close to call

DeepSeek-V3.1-Terminus: 35.7 (#138), MiMo-V2.5: 35.4 (#145)

Math benchmarks
BenchmarkDeepSeek-V3.1-TerminusMiMo-V2.5
LMArena Math14021436
ProofBench—16%

Knowledge Not comparable

DeepSeek-V3.1-Terminus: —, MiMo-V2.5: 40.2 (#109)

Knowledge benchmarks
BenchmarkDeepSeek-V3.1-TerminusMiMo-V2.5
LMArena Expert—1459

Multimodal Not comparable

DeepSeek-V3.1-Terminus: —, MiMo-V2.5: 39.0 (#53)

Multimodal benchmarks
BenchmarkDeepSeek-V3.1-TerminusMiMo-V2.5
LMArena Vision—1245

Multilingual Too close to call

DeepSeek-V3.1-Terminus: 52.3 (#87), MiMo-V2.5: 52.0 (#96)

Multilingual benchmarks
BenchmarkDeepSeek-V3.1-TerminusMiMo-V2.5
LMArena Non-English14071404
LMArena Russian14341395
LMArena Chinese—1467
LMArena French—1447
LMArena German—1421
LMArena Japanese—1304
LMArena Korean—1363
LMArena Spanish—1412

Instruction Following MiMo-V2.5 leads

DeepSeek-V3.1-Terminus: 74.4 (#96), MiMo-V2.5: 75.7 (#55)

Instruction Following benchmarks
BenchmarkDeepSeek-V3.1-TerminusMiMo-V2.5
LMArena Instruction Following14061433

Long Context Too close to call

DeepSeek-V3.1-Terminus: 43.5 (#88), MiMo-V2.5: 44.1 (#69)

Long Context benchmarks
BenchmarkDeepSeek-V3.1-TerminusMiMo-V2.5
LMArena Longer Query14261444

Writing & Preference Too close to call

DeepSeek-V3.1-Terminus: 61.3 (#87), MiMo-V2.5: 61.8 (#82)

Writing & Preference benchmarks
BenchmarkDeepSeek-V3.1-TerminusMiMo-V2.5
LMArena Text14201427
LMArena Creative Writing14041392
LMArena Multi-Turn14111445

Frequently asked questions

Is DeepSeek-V3.1-Terminus better than MiMo-V2.5?

DeepSeek-V3.1-Terminus and MiMo-V2.5 score almost the same on the Noometry Index (42.6 vs 43.0), so choose on price, context window or the category you care about most.

Which is cheaper, DeepSeek-V3.1-Terminus or MiMo-V2.5?

MiMo-V2.5 is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.30 and $1.

Is DeepSeek-V3.1-Terminus or MiMo-V2.5 better for coding?

MiMo-V2.5 scores higher on coding benchmarks: 43.6 versus 41.5 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2.5 does, with 1.05M tokens against 164K.

How many benchmarks do DeepSeek-V3.1-Terminus and MiMo-V2.5 share?

13 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and MiMo-V2.5 has 23.

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