Model comparison

GLM-5.1 vs MiMo-V2-Omni

GLM-5.1 is the stronger model overall, scoring 47.8 to 43.6 on the Noometry Index. MiMo-V2-Omni costs 12× less per token, which makes it the better buy when GLM-5.1's lead doesn't matter for your workload.

Last verified . 17 shared benchmarks.

GLM-5.1 Z.ai (Zhipu)

47.8

Rank #59 Confirmed

MiMo-V2-Omni Xiaomi

43.6

Rank #88 Confirmed

Summary

  • They share 17 benchmarks with published results for both. GLM-5.1 scores higher in 8 categories and MiMo-V2-Omni in 0 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5.1 leads 54.9 to 40.5.
  • MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $1.40 / $4.40 for GLM-5.1.
  • MiMo-V2-Omni accepts more context: 262K tokens versus 200K.
  • GLM-5.1 has downloadable open weights; the other is API-only.

Side by side

GLM-5.1 and MiMo-V2-Omni specifications
GLM-5.1MiMo-V2-Omni
ProviderZ.ai (Zhipu)Xiaomi
Noometry Index47.843.6
Released2026-04-072026-03-18
WeightsOpenProprietary
Context window200K262K
Max output131K131K
Input $ / M tokens$1.40$0.14
Output $ / M tokens$4.40$0.28
Results tracked4118

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Category by category

Coding GLM-5.1 leads

GLM-5.1: 48.7 (#55), MiMo-V2-Omni: 43.3 (#89)

Coding benchmarks
BenchmarkGLM-5.1MiMo-V2-Omni
LMArena Coding14851466
SWE-bench Verified74.2%—
LMArena WebDev1508—
SciCode43.8%—
WeirdML57.1%—
ALE-Bench887.1—

Agentic & Tool Use Not comparable

GLM-5.1: 24.9 (#113), MiMo-V2-Omni: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.1MiMo-V2-Omni
APEX-Agents40.9%—
ExploitBench18.1%—
GBAEval0%—
Vending-Bench 25,634—

Reasoning GLM-5.1 leads

GLM-5.1: 39.1 (#60), MiMo-V2-Omni: 29.7 (#88)

Reasoning benchmarks
BenchmarkGLM-5.1MiMo-V2-Omni
LMArena Hard Prompts14721445
SimpleBench55.1%—
NYT Connections (extended)77.7%—
CritPt4.6%—
Chess Puzzles19%—
Thematic Generalization69.8%—
Epoch Capabilities Index149.84—

Math GLM-5.1 leads

GLM-5.1: 49.7 (#60), MiMo-V2-Omni: 39.1 (#115)

Knowledge GLM-5.1 leads

GLM-5.1: 54.9 (#50), MiMo-V2-Omni: 40.5 (#118)

Knowledge benchmarks
BenchmarkGLM-5.1MiMo-V2-Omni
LMArena Expert14761449
GPQA Diamond89.9%—
SimpleQA Verified34%—

Multimodal Not comparable

GLM-5.1: —, MiMo-V2-Omni: 38.6 (#63)

Multimodal benchmarks
BenchmarkGLM-5.1MiMo-V2-Omni
LMArena Vision—1228

Multilingual GLM-5.1 leads

GLM-5.1: 55.0 (#36), MiMo-V2-Omni: 51.8 (#102)

Multilingual benchmarks
BenchmarkGLM-5.1MiMo-V2-Omni
LMArena Non-English14471404
LMArena Chinese15151465
LMArena French14741447
LMArena German14651399
LMArena Japanese14341317
LMArena Korean14181355
LMArena Russian14541412
LMArena Spanish14691434

Instruction Following GLM-5.1 leads

GLM-5.1: 76.3 (#42), MiMo-V2-Omni: 75.2 (#66)

Instruction Following benchmarks
BenchmarkGLM-5.1MiMo-V2-Omni
LMArena Instruction Following14511428

Long Context Too close to call

GLM-5.1: 44.9 (#53), MiMo-V2-Omni: 44.1 (#76)

Long Context benchmarks
BenchmarkGLM-5.1MiMo-V2-Omni
LMArena Longer Query14661442

Writing & Preference GLM-5.1 leads

GLM-5.1: 66.9 (#31), MiMo-V2-Omni: 61.4 (#87)

Writing & Preference benchmarks
BenchmarkGLM-5.1MiMo-V2-Omni
LMArena Text14611423
LMArena Creative Writing14531392
LMArena Multi-Turn14721445
EQ-Bench Creative Writing1592—

Frequently asked questions

Is GLM-5.1 better than MiMo-V2-Omni?

GLM-5.1 is the stronger model overall, scoring 47.8 to 43.6 on the Noometry Index. MiMo-V2-Omni costs 12× less per token, which makes it the better buy when GLM-5.1's lead doesn't matter for your workload.

Which is cheaper, GLM-5.1 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-5.1 lists at $1.40 and $4.40.

Is GLM-5.1 or MiMo-V2-Omni better for coding?

GLM-5.1 scores higher on coding benchmarks: 48.7 versus 43.3 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2-Omni does, with 262K tokens against 200K.

How many benchmarks do GLM-5.1 and MiMo-V2-Omni share?

17 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and MiMo-V2-Omni has 18.

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