Noometry

Model comparison

GLM-5.3-Flash vs MiMo-V2.5

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 43.4 on the Noometry Index.

Last verified . 23 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

MiMo-V2.5 Xiaomi

43.4

Rank #93 Confirmed

Summary

  • They share 23 benchmarks with published results for both. GLM-5.3-Flash scores higher in 9 categories and MiMo-V2.5 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 28.6.
  • The biggest single-benchmark swing is CritPt: 15.4% for GLM-5.3-Flash and 3.7% for MiMo-V2.5.
  • MiMo-V2.5 is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.15 / $0.50 for GLM-5.3-Flash.
  • MiMo-V2.5 accepts more context: 1.05M tokens versus 1M.

Side by side

GLM-5.3-FlashMiMo-V2.5
ProviderZ.ai (Zhipu)Xiaomi
Noometry Index51.843.4
Released2026-08-202026-04-22
WeightsOpenOpen
Context window1M1.05M
Max output131K131K
Input $ / M tokens$0.15$0.14
Output $ / M tokens$0.50$0.28
Results tracked4023

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), MiMo-V2.5: 43.9 (#81)

BenchmarkGLM-5.3-FlashMiMo-V2.5
LMArena WebDev16091438
SciCode51.6%43.1%
LMArena Coding15081469
ALE-Bench303.55513.95
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
FrontierSWE18.1%—

Agentic & Tool Use Not comparable

GLM-5.3-Flash: 34.2 (#47), MiMo-V2.5: —

BenchmarkGLM-5.3-FlashMiMo-V2.5
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), MiMo-V2.5: 28.6 (#101)

BenchmarkGLM-5.3-FlashMiMo-V2.5
CritPt15.4%3.7%
LMArena Hard Prompts14911450
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-V2.5: 36.8 (#163)

BenchmarkGLM-5.3-FlashMiMo-V2.5
ProofBench21%16%
LMArena Math15001436
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
OTIS Mock AIME 2024-202593.9%—

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#36), MiMo-V2.5: 40.8 (#115)

BenchmarkGLM-5.3-FlashMiMo-V2.5
LMArena Expert15131460
GPQA Diamond90.2%—

Multimodal GLM-5.3-Flash leads

GLM-5.3-Flash: 42.8 (#27), MiMo-V2.5: 39.8 (#54)

BenchmarkGLM-5.3-FlashMiMo-V2.5
LMArena Vision12961247

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), MiMo-V2.5: 51.9 (#99)

BenchmarkGLM-5.3-FlashMiMo-V2.5
LMArena Non-English14621404
LMArena Chinese15271468
LMArena French14961447
LMArena German14701421
LMArena Japanese14291306
LMArena Korean14461363
LMArena Russian14691395
LMArena Spanish14711416

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), MiMo-V2.5: 75.5 (#60)

BenchmarkGLM-5.3-FlashMiMo-V2.5
LMArena Instruction Following14781434

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.4 (#39), MiMo-V2.5: 44.2 (#73)

BenchmarkGLM-5.3-FlashMiMo-V2.5
LMArena Longer Query14821445

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), MiMo-V2.5: 61.6 (#86)

BenchmarkGLM-5.3-FlashMiMo-V2.5
LMArena Text14711428
LMArena Creative Writing14421393
LMArena Multi-Turn14671445

Frequently asked questions

Is GLM-5.3-Flash better than MiMo-V2.5?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 43.4 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or MiMo-V2.5?

MiMo-V2.5 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-V2.5 better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 43.9 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2.5 does, with 1.05M tokens against 1M.

How many benchmarks do GLM-5.3-Flash and MiMo-V2.5 share?

23 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and MiMo-V2.5 has 23.

Related comparisons

Go deeper