Model comparison

GLM-4.5V vs MiMo-V2.6-Pro

MiMo-V2.6-Pro is the stronger model overall, scoring 50.3 to 39.8 on the Noometry Index.

Last verified . 13 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

MiMo-V2.6-Pro Xiaomi

50.3

Rank #49 Confirmed

Summary

  • They share 13 benchmarks with published results for both. GLM-4.5V scores higher in 0 categories and MiMo-V2.6-Pro in 9 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where MiMo-V2.6-Pro leads 54.5 to 37.4.
  • MiMo-V2.6-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
  • MiMo-V2.6-Pro accepts more context: 1.05M tokens versus 64K.

Side by side

GLM-4.5V and MiMo-V2.6-Pro specifications
GLM-4.5VMiMo-V2.6-Pro
ProviderZ.ai (Zhipu)Xiaomi
Noometry Index39.850.3
Released2025-08-112026-09-21
WeightsOpenOpen
Context window64K1.05M
Max output16K131K
Input $ / M tokens$0.60$0.43
Output $ / M tokens$1.80$0.87
Results tracked1519

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Category by category

Coding MiMo-V2.6-Pro leads

GLM-4.5V: 39.5 (#155), MiMo-V2.6-Pro: 55.5 (#23)

Coding benchmarks
BenchmarkGLM-4.5VMiMo-V2.6-Pro
LMArena Coding13471534
LMArena WebDev—1629
SciCode—60.9%
ALE-Bench—1,158

Agentic & Tool Use Not comparable

GLM-4.5V: —, MiMo-V2.6-Pro: 37.5 (#35)

Agentic & Tool Use benchmarks
BenchmarkGLM-4.5VMiMo-V2.6-Pro
APEX-Agents—59.5%

Reasoning MiMo-V2.6-Pro leads

GLM-4.5V: 27.4 (#119), MiMo-V2.6-Pro: 43.1 (#50)

Reasoning benchmarks
BenchmarkGLM-4.5VMiMo-V2.6-Pro
LMArena Hard Prompts13341512
Kagi LLM Benchmark59.8%—
CritPt—26.6%

Math MiMo-V2.6-Pro leads

GLM-4.5V: 37.4 (#159), MiMo-V2.6-Pro: 54.5 (#45)

Math benchmarks
BenchmarkGLM-4.5VMiMo-V2.6-Pro
LMArena Math13541494
ProofBench—70%

Knowledge MiMo-V2.6-Pro leads

GLM-4.5V: 37.5 (#156), MiMo-V2.6-Pro: 43.5 (#92)

Knowledge benchmarks
BenchmarkGLM-4.5VMiMo-V2.6-Pro
LMArena Expert13531543

Multimodal MiMo-V2.6-Pro leads

GLM-4.5V: 34.3 (#92), MiMo-V2.6-Pro: 40.8 (#43)

Multimodal benchmarks
BenchmarkGLM-4.5VMiMo-V2.6-Pro
LMArena Vision11541264

Multilingual MiMo-V2.6-Pro leads

GLM-4.5V: 44.6 (#177), MiMo-V2.6-Pro: 56.9 (#14)

Multilingual benchmarks
BenchmarkGLM-4.5VMiMo-V2.6-Pro
LMArena Non-English13031474
LMArena Chinese13371529
LMArena Russian12981480
LMArena Spanish1336—

Instruction Following MiMo-V2.6-Pro leads

GLM-4.5V: 69.2 (#175), MiMo-V2.6-Pro: 78.2 (#12)

Instruction Following benchmarks
BenchmarkGLM-4.5VMiMo-V2.6-Pro
LMArena Instruction Following13111493

Long Context MiMo-V2.6-Pro leads

GLM-4.5V: 39.6 (#171), MiMo-V2.6-Pro: 46.0 (#27)

Long Context benchmarks
BenchmarkGLM-4.5VMiMo-V2.6-Pro
LMArena Longer Query13041501

Writing & Preference MiMo-V2.6-Pro leads

GLM-4.5V: 52.5 (#170), MiMo-V2.6-Pro: 66.8 (#33)

Writing & Preference benchmarks
BenchmarkGLM-4.5VMiMo-V2.6-Pro
LMArena Text13331492
LMArena Creative Writing12951468
LMArena Multi-Turn13321464

Frequently asked questions

Is GLM-4.5V better than MiMo-V2.6-Pro?

MiMo-V2.6-Pro is the stronger model overall, scoring 50.3 to 39.8 on the Noometry Index.

Which is cheaper, GLM-4.5V or MiMo-V2.6-Pro?

MiMo-V2.6-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.

Is GLM-4.5V or MiMo-V2.6-Pro better for coding?

MiMo-V2.6-Pro scores higher on coding benchmarks: 55.5 versus 39.5 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2.6-Pro does, with 1.05M tokens against 64K.

How many benchmarks do GLM-4.5V and MiMo-V2.6-Pro share?

13 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and MiMo-V2.6-Pro has 19.

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