Noometry

Model comparison

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

MiMo-V2.6-Pro is the stronger model overall, scoring 50.3 to 38.9 on the Noometry Index.

Last verified . 12 shared benchmarks.

GLM-4.5-Air Z.ai (Zhipu)

38.9

Rank #177 Confirmed

MiMo-V2.6-Pro Xiaomi

50.3

Rank #49 Confirmed

Summary

  • They share 12 benchmarks with published results for both. GLM-4.5-Air scores higher in 0 categories and MiMo-V2.6-Pro in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in coding, where MiMo-V2.6-Pro leads 55.5 to 33.3.
  • GLM-4.5-Air is cheaper at $0.20 / $1.10 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2.6-Pro.
  • MiMo-V2.6-Pro accepts more context: 1.05M tokens versus 131K.

Side by side

GLM-4.5-AirMiMo-V2.6-Pro
ProviderZ.ai (Zhipu)Xiaomi
Noometry Index38.950.3
Released2025-07-202026-09-21
WeightsOpenOpen
Context window131K1.05M
Max output98K131K
Input $ / M tokens$0.20$0.43
Output $ / M tokens$1.10$0.87
Results tracked2719

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Category by category

Coding MiMo-V2.6-Pro leads

GLM-4.5-Air: 33.3 (#259), MiMo-V2.6-Pro: 55.5 (#23)

BenchmarkGLM-4.5-AirMiMo-V2.6-Pro
LMArena Coding13971534
LMArena WebDev—1629
SciCode—60.9%
GSO2.9%—
ALE-Bench—1,158

Agentic & Tool Use Not comparable

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

BenchmarkGLM-4.5-AirMiMo-V2.6-Pro
APEX-Agents—59.5%

Reasoning MiMo-V2.6-Pro leads

GLM-4.5-Air: 24.1 (#166), MiMo-V2.6-Pro: 43.1 (#50)

BenchmarkGLM-4.5-AirMiMo-V2.6-Pro
LMArena Hard Prompts13791512
Kagi LLM Benchmark43%—
CritPt—26.6%
ForecastBench59.2—

Math MiMo-V2.6-Pro leads

GLM-4.5-Air: 36.2 (#170), MiMo-V2.6-Pro: 54.5 (#45)

BenchmarkGLM-4.5-AirMiMo-V2.6-Pro
LMArena Math13961494
ProofBench—70%
Omni-MATH39.1%—

Knowledge MiMo-V2.6-Pro leads

GLM-4.5-Air: 35.0 (#191), MiMo-V2.6-Pro: 43.5 (#92)

BenchmarkGLM-4.5-AirMiMo-V2.6-Pro
LMArena Expert13701543
Humanity's Last Exam8.1%—
MMLU-Pro76.2%—
Vectara Hallucination Rate9.3%—
GPQA (HELM)59.4%—

Multimodal Not comparable

GLM-4.5-Air: —, MiMo-V2.6-Pro: 40.8 (#43)

BenchmarkGLM-4.5-AirMiMo-V2.6-Pro
LMArena Vision—1264

Multilingual MiMo-V2.6-Pro leads

GLM-4.5-Air: 49.1 (#135), MiMo-V2.6-Pro: 56.9 (#14)

BenchmarkGLM-4.5-AirMiMo-V2.6-Pro
LMArena Non-English13661474
LMArena Chinese14261529
LMArena Russian13731480
LMArena French1399—
LMArena German1377—
LMArena Japanese1348—
LMArena Korean1308—
LMArena Spanish1386—

Instruction Following MiMo-V2.6-Pro leads

GLM-4.5-Air: 69.6 (#171), MiMo-V2.6-Pro: 78.2 (#12)

BenchmarkGLM-4.5-AirMiMo-V2.6-Pro
LMArena Instruction Following13541493
IFEval81.2%—

Long Context MiMo-V2.6-Pro leads

GLM-4.5-Air: 41.6 (#135), MiMo-V2.6-Pro: 46.0 (#27)

BenchmarkGLM-4.5-AirMiMo-V2.6-Pro
LMArena Longer Query13661501

Writing & Preference MiMo-V2.6-Pro leads

GLM-4.5-Air: 55.9 (#139), MiMo-V2.6-Pro: 66.8 (#33)

BenchmarkGLM-4.5-AirMiMo-V2.6-Pro
LMArena Text13841492
LMArena Creative Writing13431468
LMArena Multi-Turn13711464
WildBench78.9%—

Frequently asked questions

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

MiMo-V2.6-Pro is the stronger model overall, scoring 50.3 to 38.9 on the Noometry Index.

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

GLM-4.5-Air is cheaper. It lists at $0.20 per million input tokens and $1.10 per million output tokens; MiMo-V2.6-Pro lists at $0.43 and $0.87.

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

MiMo-V2.6-Pro scores higher on coding benchmarks: 55.5 versus 33.3 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2.6-Pro does, with 1.05M tokens against 131K.

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

12 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and MiMo-V2.6-Pro has 19.

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