Noometry

Model comparison

GLM-4.7 vs MiMo-V2.5

MiMo-V2.5 is the stronger model overall, scoring 43.0 to 41.7 on the Noometry Index.

Last verified . 22 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

41.7

Rank #117 Confirmed

MiMo-V2.5 Xiaomi

43.0

Rank #89 Confirmed

Summary

  • They share 22 benchmarks with published results for both. GLM-4.7 scores higher in 4 categories and MiMo-V2.5 in 4 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 40.2.
  • The biggest single-benchmark swing is ProofBench: 6% for GLM-4.7 and 16% for MiMo-V2.5.
  • MiMo-V2.5 is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.
  • MiMo-V2.5 accepts more context: 1.05M tokens versus 205K.

Side by side

GLM-4.7MiMo-V2.5
ProviderZ.ai (Zhipu)Xiaomi
Noometry Index41.743.0
Released2025-12-222026-04-22
WeightsOpenOpen
Context window205K1.05M
Max output131K131K
Input $ / M tokens$0.60$0.14
Output $ / M tokens$2.20$0.28
Results tracked3623

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Category by category

Coding Too close to call

GLM-4.7: 43.6 (#74), MiMo-V2.5: 43.6 (#75)

BenchmarkGLM-4.7MiMo-V2.5
LMArena WebDev14351438
SciCode45.1%43.1%
LMArena Coding14541469
ALE-Bench399.48513.95

Agentic & Tool Use Not comparable

GLM-4.7: 26.4 (#96), MiMo-V2.5: —

BenchmarkGLM-4.7MiMo-V2.5
Terminal-Bench33.4%—
Vending-Bench 22,377—

Reasoning MiMo-V2.5 leads

GLM-4.7: 23.7 (#161), MiMo-V2.5: 27.8 (#98)

BenchmarkGLM-4.7MiMo-V2.5
CritPt1.7%3.7%
LMArena Hard Prompts14431450
SimpleBench47.7%—
Chess Puzzles6%—
Epoch Capabilities Index143.53—

Math GLM-4.7 leads

GLM-4.7: 37.7 (#92), MiMo-V2.5: 35.4 (#145)

BenchmarkGLM-4.7MiMo-V2.5
ProofBench6%16%
LMArena Math14231436
OTIS Mock AIME 2024-202583.3%—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#74), MiMo-V2.5: 40.2 (#109)

BenchmarkGLM-4.7MiMo-V2.5
LMArena Expert14241459
GPQA Diamond83.3%—
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—

Multimodal Not comparable

GLM-4.7: —, MiMo-V2.5: 39.0 (#53)

BenchmarkGLM-4.7MiMo-V2.5
LMArena Vision—1245

Multilingual Too close to call

GLM-4.7: 53.0 (#75), MiMo-V2.5: 52.0 (#96)

BenchmarkGLM-4.7MiMo-V2.5
LMArena Non-English14171404
LMArena Chinese14951467
LMArena French14321447
LMArena German14261421
LMArena Japanese14391304
LMArena Korean14011363
LMArena Russian14231395
LMArena Spanish14331412

Instruction Following MiMo-V2.5 leads

GLM-4.7: 74.6 (#90), MiMo-V2.5: 75.7 (#55)

BenchmarkGLM-4.7MiMo-V2.5
LMArena Instruction Following14111433

Long Context MiMo-V2.5 leads

GLM-4.7: 42.8 (#111), MiMo-V2.5: 44.1 (#69)

BenchmarkGLM-4.7MiMo-V2.5
LMArena Longer Query14321444
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference Too close to call

GLM-4.7: 61.1 (#89), MiMo-V2.5: 61.8 (#82)

BenchmarkGLM-4.7MiMo-V2.5
LMArena Text14361427
LMArena Creative Writing14011392
LMArena Multi-Turn14461445
EQ-Bench Creative Writing1413—

Frequently asked questions

Is GLM-4.7 better than MiMo-V2.5?

MiMo-V2.5 is the stronger model overall, scoring 43.0 to 41.7 on the Noometry Index.

Which is cheaper, GLM-4.7 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; GLM-4.7 lists at $0.60 and $2.20.

Is GLM-4.7 or MiMo-V2.5 better for coding?

They score almost the same on coding (43.6 vs 43.6); test both on your own repository before choosing.

Which has the bigger context window?

MiMo-V2.5 does, with 1.05M tokens against 205K.

How many benchmarks do GLM-4.7 and MiMo-V2.5 share?

22 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and MiMo-V2.5 has 23.

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