Model comparison

GLM-4.5V vs MiMo-V2-Omni

MiMo-V2-Omni is the stronger model overall, scoring 42.9 to 39.2 on the Noometry Index.

Last verified . 14 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.2

Rank #158 Confirmed

MiMo-V2-Omni Xiaomi

42.9

Rank #91 Confirmed

Summary

  • They share 14 benchmarks with published results for both. GLM-4.5V scores higher in 0 categories and MiMo-V2-Omni in 9 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where MiMo-V2-Omni leads 61.6 to 52.7.
  • MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
  • MiMo-V2-Omni accepts more context: 262K tokens versus 64K.
  • GLM-4.5V has downloadable open weights; the other is API-only.

Side by side

GLM-4.5V and MiMo-V2-Omni specifications
GLM-4.5VMiMo-V2-Omni
ProviderZ.ai (Zhipu)Xiaomi
Noometry Index39.242.9
Released2025-08-112026-03-18
WeightsOpenProprietary
Context window64K262K
Max output16K131K
Input $ / M tokens$0.60$0.14
Output $ / M tokens$1.80$0.28
Results tracked1518

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Category by category

Coding MiMo-V2-Omni leads

GLM-4.5V: 38.9 (#152), MiMo-V2-Omni: 42.7 (#87)

Coding benchmarks
BenchmarkGLM-4.5VMiMo-V2-Omni
LMArena Coding13471467

Reasoning MiMo-V2-Omni leads

GLM-4.5V: 26.5 (#118), MiMo-V2-Omni: 28.6 (#86)

Reasoning benchmarks
BenchmarkGLM-4.5VMiMo-V2-Omni
LMArena Hard Prompts13351445
Kagi LLM Benchmark59.8%—

Math MiMo-V2-Omni leads

GLM-4.5V: 34.7 (#157), MiMo-V2-Omni: 36.4 (#112)

Math benchmarks
BenchmarkGLM-4.5VMiMo-V2-Omni
LMArena Math13531432

Knowledge MiMo-V2-Omni leads

GLM-4.5V: 36.8 (#155), MiMo-V2-Omni: 39.9 (#114)

Knowledge benchmarks
BenchmarkGLM-4.5VMiMo-V2-Omni
LMArena Expert13531449

Multimodal MiMo-V2-Omni leads

GLM-4.5V: 33.6 (#86), MiMo-V2-Omni: 37.9 (#62)

Multimodal benchmarks
BenchmarkGLM-4.5VMiMo-V2-Omni
LMArena Vision11541228

Multilingual MiMo-V2-Omni leads

GLM-4.5V: 44.9 (#172), MiMo-V2-Omni: 52.0 (#97)

Multilingual benchmarks
BenchmarkGLM-4.5VMiMo-V2-Omni
LMArena Non-English13041404
LMArena Chinese13381469
LMArena Russian12991412
LMArena Spanish13351432
LMArena French—1448
LMArena German—1398
LMArena Japanese—1318
LMArena Korean—1355

Instruction Following MiMo-V2-Omni leads

GLM-4.5V: 69.4 (#170), MiMo-V2-Omni: 75.4 (#62)

Instruction Following benchmarks
BenchmarkGLM-4.5VMiMo-V2-Omni
LMArena Instruction Following13111428

Long Context MiMo-V2-Omni leads

GLM-4.5V: 39.6 (#166), MiMo-V2-Omni: 44.1 (#72)

Long Context benchmarks
BenchmarkGLM-4.5VMiMo-V2-Omni
LMArena Longer Query13051442

Writing & Preference MiMo-V2-Omni leads

GLM-4.5V: 52.7 (#162), MiMo-V2-Omni: 61.6 (#83)

Writing & Preference benchmarks
BenchmarkGLM-4.5VMiMo-V2-Omni
LMArena Text13331424
LMArena Creative Writing12951393
LMArena Multi-Turn13331446

Frequently asked questions

Is GLM-4.5V better than MiMo-V2-Omni?

MiMo-V2-Omni is the stronger model overall, scoring 42.9 to 39.2 on the Noometry Index.

Which is cheaper, GLM-4.5V or MiMo-V2-Omni?

MiMo-V2-Omni is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.

Is GLM-4.5V or MiMo-V2-Omni better for coding?

MiMo-V2-Omni scores higher on coding benchmarks: 42.7 versus 38.9 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2-Omni does, with 262K tokens against 64K.

How many benchmarks do GLM-4.5V and MiMo-V2-Omni share?

14 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and MiMo-V2-Omni has 18.

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