Noometry

Model comparison

GLM-4.7 vs MiMo-V2-Pro

MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 42.0 on the Noometry Index.

Last verified . 21 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

MiMo-V2-Pro Xiaomi

43.0

Rank #103 Confirmed

Summary

  • They share 21 benchmarks with published results for both. GLM-4.7 scores higher in 5 categories and MiMo-V2-Pro in 3 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 41.4.
  • MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.
  • MiMo-V2-Pro accepts more context: 1.05M tokens versus 205K.
  • GLM-4.7 has downloadable open weights; the other is API-only.

Side by side

GLM-4.7MiMo-V2-Pro
ProviderZ.ai (Zhipu)Xiaomi
Noometry Index42.043.0
Released2025-12-222026-03-18
WeightsOpenProprietary
Context window205K1.05M
Max output131K131K
Input $ / M tokens$0.60$0.43
Output $ / M tokens$2.20$0.87
Results tracked3623

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

Category by category

Coding Too close to call

GLM-4.7: 44.0 (#79), MiMo-V2-Pro: 43.8 (#83)

BenchmarkGLM-4.7MiMo-V2-Pro
LMArena WebDev14351433
LMArena Coding14541476
ALE-Bench399.48785.17
SciCode45.1%—

Agentic & Tool Use Not comparable

GLM-4.7: 26.5 (#103), MiMo-V2-Pro: —

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

Reasoning GLM-4.7 leads

GLM-4.7: 24.3 (#164), MiMo-V2-Pro: 22.1 (#206)

BenchmarkGLM-4.7MiMo-V2-Pro
LMArena Hard Prompts14431457
SimpleBench47.7%—
NYT Connections (extended)—25.8%
CritPt1.7%—
Chess Puzzles6%—
Thematic Generalization—45.9%
Epoch Capabilities Index143.51—

Math Too close to call

GLM-4.7: 38.6 (#135), MiMo-V2-Pro: 39.5 (#102)

BenchmarkGLM-4.7MiMo-V2-Pro
LMArena Math14231447
OTIS Mock AIME 2024-202583.3%—
ProofBench6%—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#80), MiMo-V2-Pro: 41.4 (#111)

BenchmarkGLM-4.7MiMo-V2-Pro
LMArena Expert14241478
GPQA Diamond83.3%—
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—

Multilingual Too close to call

GLM-4.7: 52.8 (#79), MiMo-V2-Pro: 52.7 (#81)

BenchmarkGLM-4.7MiMo-V2-Pro
LMArena Non-English14171416
LMArena Chinese14951456
LMArena French14321469
LMArena German14241417
LMArena Japanese14391366
LMArena Korean13991400
LMArena Russian14231427
LMArena Spanish14341457

Instruction Following MiMo-V2-Pro leads

GLM-4.7: 74.4 (#95), MiMo-V2-Pro: 76.0 (#49)

BenchmarkGLM-4.7MiMo-V2-Pro
LMArena Instruction Following14111445

Long Context GLM-4.7 leads

GLM-4.7: 42.8 (#116), MiMo-V2-Pro: 41.5 (#138)

BenchmarkGLM-4.7MiMo-V2-Pro
CL-bench15.9%15.7%
CL-bench Life10.9%6.9%
LMArena Longer Query14321455

Writing & Preference MiMo-V2-Pro leads

GLM-4.7: 60.9 (#93), MiMo-V2-Pro: 62.8 (#70)

BenchmarkGLM-4.7MiMo-V2-Pro
LMArena Text14351436
LMArena Creative Writing14011415
LMArena Multi-Turn14461456
EQ-Bench Creative Writing1413—

Frequently asked questions

Is GLM-4.7 better than MiMo-V2-Pro?

MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 42.0 on the Noometry Index.

Which is cheaper, GLM-4.7 or MiMo-V2-Pro?

MiMo-V2-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; GLM-4.7 lists at $0.60 and $2.20.

Is GLM-4.7 or MiMo-V2-Pro better for coding?

They score almost the same on coding (44.0 vs 43.8); test both on your own repository before choosing.

Which has the bigger context window?

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

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

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

Related comparisons

Go deeper