Noometry

Model comparison

GLM-5.3-Flash vs MiMo-V2-Omni

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 43.6 on the Noometry Index.

Last verified . 18 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

MiMo-V2-Omni Xiaomi

43.6

Rank #88 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-5.3-Flash scores higher in 9 categories and MiMo-V2-Omni in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5.3-Flash leads 48.0 to 29.7.
  • MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.15 / $0.50 for GLM-5.3-Flash.
  • GLM-5.3-Flash accepts more context: 1M tokens versus 262K.
  • GLM-5.3-Flash has downloadable open weights; the other is API-only.

Side by side

GLM-5.3-FlashMiMo-V2-Omni
ProviderZ.ai (Zhipu)Xiaomi
Noometry Index51.843.6
Released2026-08-202026-03-18
WeightsOpenProprietary
Context window1M262K
Max output131K131K
Input $ / M tokens$0.15$0.14
Output $ / M tokens$0.50$0.28
Results tracked4018

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), MiMo-V2-Omni: 43.3 (#89)

BenchmarkGLM-5.3-FlashMiMo-V2-Omni
LMArena Coding15081466
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
LMArena WebDev1609—
FrontierSWE18.1%—
SciCode51.6%—
ALE-Bench303.55—

Agentic & Tool Use Not comparable

GLM-5.3-Flash: 34.2 (#47), MiMo-V2-Omni: —

BenchmarkGLM-5.3-FlashMiMo-V2-Omni
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), MiMo-V2-Omni: 29.7 (#88)

BenchmarkGLM-5.3-FlashMiMo-V2-Omni
LMArena Hard Prompts14911445
ARC-AGI-265.8%—
ARC-AGI-191%—
CritPt15.4%—
Chess Puzzles14%—
Mystery Game Puzzles8%—
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
Epoch Capabilities Index151.88—

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.3 (#47), MiMo-V2-Omni: 39.1 (#115)

BenchmarkGLM-5.3-FlashMiMo-V2-Omni
LMArena Math15001430
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
OTIS Mock AIME 2024-202593.9%—
ProofBench21%—

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#36), MiMo-V2-Omni: 40.5 (#118)

BenchmarkGLM-5.3-FlashMiMo-V2-Omni
LMArena Expert15131449
GPQA Diamond90.2%—

Multimodal GLM-5.3-Flash leads

GLM-5.3-Flash: 42.8 (#27), MiMo-V2-Omni: 38.6 (#63)

BenchmarkGLM-5.3-FlashMiMo-V2-Omni
LMArena Vision12961228

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), MiMo-V2-Omni: 51.8 (#102)

BenchmarkGLM-5.3-FlashMiMo-V2-Omni
LMArena Non-English14621404
LMArena Chinese15271465
LMArena French14961447
LMArena German14701399
LMArena Japanese14291317
LMArena Korean14461355
LMArena Russian14691412
LMArena Spanish14711434

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), MiMo-V2-Omni: 75.2 (#66)

BenchmarkGLM-5.3-FlashMiMo-V2-Omni
LMArena Instruction Following14781428

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.4 (#39), MiMo-V2-Omni: 44.1 (#76)

BenchmarkGLM-5.3-FlashMiMo-V2-Omni
LMArena Longer Query14821442

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), MiMo-V2-Omni: 61.4 (#87)

BenchmarkGLM-5.3-FlashMiMo-V2-Omni
LMArena Text14711423
LMArena Creative Writing14421392
LMArena Multi-Turn14671445

Frequently asked questions

Is GLM-5.3-Flash better than MiMo-V2-Omni?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 43.6 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash 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-5.3-Flash lists at $0.15 and $0.50.

Is GLM-5.3-Flash or MiMo-V2-Omni better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 43.3 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 262K.

How many benchmarks do GLM-5.3-Flash and MiMo-V2-Omni share?

18 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and MiMo-V2-Omni has 18.

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