Noometry

Model comparison

GLM-4.5 vs MiMo-V2.6-Pro

MiMo-V2.6-Pro is the stronger model overall, scoring 50.3 to 42.0 on the Noometry Index.

Last verified . 13 shared benchmarks.

GLM-4.5 Z.ai (Zhipu)

42.0

Rank #122 Confirmed

MiMo-V2.6-Pro Xiaomi

50.3

Rank #49 Confirmed

Summary

  • They share 13 benchmarks with published results for both. GLM-4.5 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 math, where MiMo-V2.6-Pro leads 54.5 to 39.0.
  • MiMo-V2.6-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
  • MiMo-V2.6-Pro accepts more context: 1.05M tokens versus 131K.

Side by side

GLM-4.5MiMo-V2.6-Pro
ProviderZ.ai (Zhipu)Xiaomi
Noometry Index42.050.3
Released2025-07-272026-09-21
WeightsOpenOpen
Context window131K1.05M
Max output98K131K
Input $ / M tokens$0.60$0.43
Output $ / M tokens$2.20$0.87
Results tracked2719

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Category by category

Coding MiMo-V2.6-Pro leads

GLM-4.5: 41.4 (#125), MiMo-V2.6-Pro: 55.5 (#23)

BenchmarkGLM-4.5MiMo-V2.6-Pro
LMArena Coding14341534
ALE-Bench344.821,158
SWE-bench Verified (bash only)54.2%—
LMArena WebDev—1629
SciCode—60.9%
WeirdML40.6%—
AlgoTune1.52—

Agentic & Tool Use Not comparable

GLM-4.5: —, MiMo-V2.6-Pro: 37.5 (#35)

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

Reasoning MiMo-V2.6-Pro leads

GLM-4.5: 28.6 (#100), MiMo-V2.6-Pro: 43.1 (#50)

BenchmarkGLM-4.5MiMo-V2.6-Pro
LMArena Hard Prompts14291512
Kagi LLM Benchmark57.9%—
CritPt—26.6%

Math MiMo-V2.6-Pro leads

GLM-4.5: 39.0 (#116), MiMo-V2.6-Pro: 54.5 (#45)

BenchmarkGLM-4.5MiMo-V2.6-Pro
LMArena Math14271494
ProofBench—70%

Knowledge MiMo-V2.6-Pro leads

GLM-4.5: 35.9 (#179), MiMo-V2.6-Pro: 43.5 (#92)

BenchmarkGLM-4.5MiMo-V2.6-Pro
LMArena Expert14331543
Humanity's Last Exam8.3%—
Confabulations11.3%—

Multimodal Not comparable

GLM-4.5: —, MiMo-V2.6-Pro: 40.8 (#43)

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

Multilingual MiMo-V2.6-Pro leads

GLM-4.5: 52.8 (#77), MiMo-V2.6-Pro: 56.9 (#14)

BenchmarkGLM-4.5MiMo-V2.6-Pro
LMArena Non-English14171474
LMArena Chinese14651529
LMArena Russian14141480
LMArena French1418—
LMArena German1407—
LMArena Japanese1415—
LMArena Korean1380—
LMArena Spanish1454—

Instruction Following MiMo-V2.6-Pro leads

GLM-4.5: 74.1 (#104), MiMo-V2.6-Pro: 78.2 (#12)

BenchmarkGLM-4.5MiMo-V2.6-Pro
LMArena Instruction Following14041493

Long Context MiMo-V2.6-Pro leads

GLM-4.5: 38.2 (#201), MiMo-V2.6-Pro: 46.0 (#27)

BenchmarkGLM-4.5MiMo-V2.6-Pro
LMArena Longer Query14121501
Fiction.LiveBench58.3%—

Writing & Preference MiMo-V2.6-Pro leads

GLM-4.5: 57.5 (#127), MiMo-V2.6-Pro: 66.8 (#33)

BenchmarkGLM-4.5MiMo-V2.6-Pro
LMArena Text14301492
LMArena Creative Writing13951468
LMArena Multi-Turn14151464
Short-Story Creative Writing73.4%—
EQ-Bench Creative Writing1343—

Frequently asked questions

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

MiMo-V2.6-Pro is the stronger model overall, scoring 50.3 to 42.0 on the Noometry Index.

Which is cheaper, GLM-4.5 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-4.5 lists at $0.60 and $2.20.

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

MiMo-V2.6-Pro scores higher on coding benchmarks: 55.5 versus 41.4 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 and MiMo-V2.6-Pro share?

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

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