Model comparison

MiMo-V2-Pro vs MiniMax-M2.5

MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 38.3 on the Noometry Index.

Last verified . 22 shared benchmarks.

MiMo-V2-Pro Xiaomi

43.0

Rank #103 Confirmed

MiniMax-M2.5 MiniMax

38.3

Rank #188 Confirmed

Summary

  • They share 22 benchmarks with published results for both. MiMo-V2-Pro scores higher in 7 categories and MiniMax-M2.5 in 1 category; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where MiMo-V2-Pro leads 39.5 to 26.9.
  • The biggest single-benchmark swing is NYT Connections (extended): 25.8% for MiMo-V2-Pro and 16.8% for MiniMax-M2.5.
  • Both cost about the same: $0.43 input and $0.87 output per million tokens.
  • MiMo-V2-Pro accepts more context: 1.05M tokens versus 205K.
  • MiniMax-M2.5 has downloadable open weights; the other is API-only.

Side by side

MiMo-V2-Pro and MiniMax-M2.5 specifications
MiMo-V2-ProMiniMax-M2.5
ProviderXiaomiMiniMax
Noometry Index43.038.3
Released2026-03-182026-02-12
WeightsProprietaryOpen
Context window1.05M205K
Max output131K131K
Input $ / M tokens$0.43$0.30
Output $ / M tokens$0.87$1.20
Results tracked2333

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Category by category

Coding MiniMax-M2.5 leads

MiMo-V2-Pro: 43.8 (#83), MiniMax-M2.5: 48.1 (#58)

Coding benchmarks
BenchmarkMiMo-V2-ProMiniMax-M2.5
LMArena WebDev14331387
LMArena Coding14761381
ALE-Bench785.17618.17
SWE-bench Verified (bash only)—75.8%
SWE-bench Multilingual—68.3%

Agentic & Tool Use Not comparable

MiMo-V2-Pro: —, MiniMax-M2.5: 30.4 (#77)

Agentic & Tool Use benchmarks
BenchmarkMiMo-V2-ProMiniMax-M2.5
Terminal-Bench—42.7%
Vending-Bench 2—-23.16

Reasoning MiMo-V2-Pro leads

MiMo-V2-Pro: 22.1 (#206), MiniMax-M2.5: 17.5 (#292)

Reasoning benchmarks
BenchmarkMiMo-V2-ProMiniMax-M2.5
NYT Connections (extended)25.8%16.8%
LMArena Hard Prompts14571372
ARC-AGI-2—4.9%
Kagi LLM Benchmark—55.2%
ARC-AGI-1—63.7%
Thematic Generalization45.9%—
Epoch Capabilities Index—146.68

Math MiMo-V2-Pro leads

MiMo-V2-Pro: 39.5 (#102), MiniMax-M2.5: 26.9 (#253)

Math benchmarks
BenchmarkMiMo-V2-ProMiniMax-M2.5
LMArena Math14471378
ProofBench—4%

Knowledge MiMo-V2-Pro leads

MiMo-V2-Pro: 41.4 (#111), MiniMax-M2.5: 39.2 (#135)

Knowledge benchmarks
BenchmarkMiMo-V2-ProMiniMax-M2.5
LMArena Expert14781379
Vectara Hallucination Rate—9.1%

Multilingual MiMo-V2-Pro leads

MiMo-V2-Pro: 52.7 (#81), MiniMax-M2.5: 47.1 (#152)

Multilingual benchmarks
BenchmarkMiMo-V2-ProMiniMax-M2.5
LMArena Non-English14161338
LMArena Chinese14561393
LMArena French14691362
LMArena German14171362
LMArena Japanese13661171
LMArena Korean14001232
LMArena Russian14271358
LMArena Spanish14571354

Instruction Following MiMo-V2-Pro leads

MiMo-V2-Pro: 76.0 (#49), MiniMax-M2.5: 71.5 (#148)

Instruction Following benchmarks
BenchmarkMiMo-V2-ProMiniMax-M2.5
LMArena Instruction Following14451353

Long Context MiMo-V2-Pro leads

MiMo-V2-Pro: 41.5 (#138), MiniMax-M2.5: 37.5 (#216)

Long Context benchmarks
BenchmarkMiMo-V2-ProMiniMax-M2.5
CL-bench15.7%11.4%
CL-bench Life6.9%6.3%
LMArena Longer Query14551366

Writing & Preference MiMo-V2-Pro leads

MiMo-V2-Pro: 62.8 (#70), MiniMax-M2.5: 53.9 (#153)

Writing & Preference benchmarks
BenchmarkMiMo-V2-ProMiniMax-M2.5
LMArena Text14361359
LMArena Creative Writing14151331
LMArena Multi-Turn14561364
EQ-Bench Creative Writing—1361

Frequently asked questions

Is MiMo-V2-Pro better than MiniMax-M2.5?

MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 38.3 on the Noometry Index.

Which is cheaper, MiMo-V2-Pro or MiniMax-M2.5?

MiniMax-M2.5 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; MiMo-V2-Pro lists at $0.43 and $0.87.

Is MiMo-V2-Pro or MiniMax-M2.5 better for coding?

MiniMax-M2.5 scores higher on coding benchmarks: 48.1 versus 43.8 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2-Pro does, with 1.05M tokens against 205K.

How many benchmarks do MiMo-V2-Pro and MiniMax-M2.5 share?

22 benchmarks have published results for both models. MiMo-V2-Pro has 23 scored results on Noometry and MiniMax-M2.5 has 33.

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