Noometry

Model comparison

GLM-5.3-Flash vs MiMo-V2-Flash

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 41.3 on the Noometry Index.

Last verified . 21 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

MiMo-V2-Flash Xiaomi

41.3

Rank #138 Confirmed

Summary

  • They share 21 benchmarks with published results for both. GLM-5.3-Flash scores higher in 8 categories and MiMo-V2-Flash in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5.3-Flash leads 48.0 to 24.9.
  • The biggest single-benchmark swing is SciCode: 51.6% for GLM-5.3-Flash and 25.9% for MiMo-V2-Flash.
  • MiMo-V2-Flash 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.

Side by side

GLM-5.3-FlashMiMo-V2-Flash
ProviderZ.ai (Zhipu)Xiaomi
Noometry Index51.841.3
Released2026-08-202025-12-16
WeightsOpenOpen
Context window1M262K
Max output131K66K
Input $ / M tokens$0.15$0.14
Output $ / M tokens$0.50$0.28
Results tracked4021

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), MiMo-V2-Flash: 36.1 (#211)

BenchmarkGLM-5.3-FlashMiMo-V2-Flash
LMArena WebDev16091330
SciCode51.6%25.9%
LMArena Coding15081443
ALE-Bench303.55737.95
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
FrontierSWE18.1%—

Agentic & Tool Use Not comparable

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

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

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), MiMo-V2-Flash: 24.9 (#157)

BenchmarkGLM-5.3-FlashMiMo-V2-Flash
CritPt15.4%0%
LMArena Hard Prompts14911420
ARC-AGI-265.8%—
ARC-AGI-191%—
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-Flash: 38.3 (#139)

BenchmarkGLM-5.3-FlashMiMo-V2-Flash
LMArena Math15001396
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-Flash: 39.7 (#131)

BenchmarkGLM-5.3-FlashMiMo-V2-Flash
LMArena Expert15131425
GPQA Diamond90.2%—

Multimodal Not comparable

GLM-5.3-Flash: 42.8 (#27), MiMo-V2-Flash: —

BenchmarkGLM-5.3-FlashMiMo-V2-Flash
LMArena Vision1296—

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), MiMo-V2-Flash: 51.0 (#113)

BenchmarkGLM-5.3-FlashMiMo-V2-Flash
LMArena Non-English14621392
LMArena Chinese15271462
LMArena French14961429
LMArena German14701395
LMArena Japanese14291325
LMArena Korean14461358
LMArena Russian14691387
LMArena Spanish14711420

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), MiMo-V2-Flash: 73.5 (#120)

BenchmarkGLM-5.3-FlashMiMo-V2-Flash
LMArena Instruction Following14781392

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.4 (#39), MiMo-V2-Flash: 43.0 (#110)

BenchmarkGLM-5.3-FlashMiMo-V2-Flash
LMArena Longer Query14821409

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), MiMo-V2-Flash: 59.7 (#106)

BenchmarkGLM-5.3-FlashMiMo-V2-Flash
LMArena Text14711411
LMArena Creative Writing14421375
LMArena Multi-Turn14671404

Frequently asked questions

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

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 41.3 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or MiMo-V2-Flash?

MiMo-V2-Flash 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-Flash better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 36.1 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-Flash share?

21 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and MiMo-V2-Flash has 21.

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