Noometry

Model comparison

GLM-4.5V vs o3-mini

GLM-4.5V is the stronger model overall, scoring 39.8 to 36.7 on the Noometry Index.

Last verified . 13 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

o3-mini OpenAI

36.7

Rank #212 Confirmed

Summary

  • They share 13 benchmarks with published results for both. GLM-4.5V scores higher in 4 categories and o3-mini in 4 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-4.5V leads 27.4 to 16.3.
  • GLM-4.5V is cheaper at $0.60 / $1.80 per million input/output tokens, against $1.10 / $4.40 for o3-mini.
  • o3-mini accepts more context: 200K tokens versus 64K.
  • GLM-4.5V has downloadable open weights; the other is API-only.

Side by side

GLM-4.5Vo3-mini
ProviderZ.ai (Zhipu)OpenAI
Noometry Index39.836.7
Released2025-08-112024-12-20
WeightsOpenProprietary
Context window64K200K
Max output16K100K
Input $ / M tokens$0.60$1.10
Output $ / M tokens$1.80$4.40
Results tracked1551

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Category by category

Coding o3-mini leads

GLM-4.5V: 39.5 (#155), o3-mini: 40.8 (#132)

BenchmarkGLM-4.5Vo3-mini
LMArena Coding13471378
Aider Polyglot—60.4%
SciCode—39.8%
GSO—1.3%
WeirdML—43.7%
LiveBench Coding—82.7%
CadEval—54%

Agentic & Tool Use Not comparable

GLM-4.5V: —, o3-mini: 29.6 (#84)

BenchmarkGLM-4.5Vo3-mini
Cybench—22.5%

Reasoning GLM-4.5V leads

GLM-4.5V: 27.4 (#119), o3-mini: 16.3 (#305)

BenchmarkGLM-4.5Vo3-mini
LMArena Hard Prompts13341366
ARC-AGI-2—3%
SimpleBench—22.8%
Kagi LLM Benchmark59.8%—
ARC-AGI-1—34.5%
CritPt—0.3%
Chess Puzzles—17%
LiveBench Reasoning—89.6%
Mystery Game Puzzles—7%
DTBench—68.8%
LiveBench Data Analysis—70.6%
LMCA—19%
Epoch Capabilities Index—140.34
ForecastBench—59.6
LiveBench—75.9%

Math GLM-4.5V leads

GLM-4.5V: 37.4 (#159), o3-mini: 28.1 (#244)

BenchmarkGLM-4.5Vo3-mini
LMArena Math13541396
FrontierMath (Tiers 1-3)—18.6%
FrontierMath Tier 4—0%
OTIS Mock AIME 2024-2025—76.9%
LiveBench Math—77.3%
MATH Level 5—96.5%
FrontierMath (Feb 2025 set)—12.4%
FrontierMath Tier 4 (v1)—4.2%

Knowledge Too close to call

GLM-4.5V: 37.5 (#156), o3-mini: 38.3 (#146)

BenchmarkGLM-4.5Vo3-mini
LMArena Expert13531364
GPQA Diamond—77%
SimpleQA Verified—15.3%
Confabulations—17.9%

Multimodal Not comparable

GLM-4.5V: 34.3 (#92), o3-mini: —

BenchmarkGLM-4.5Vo3-mini
LMArena Vision1154—

Multilingual o3-mini leads

GLM-4.5V: 44.6 (#177), o3-mini: 45.7 (#164)

BenchmarkGLM-4.5Vo3-mini
LMArena Non-English13031319
LMArena Chinese13371379
LMArena Russian12981304
LMArena Spanish13361321
LMArena French—1334
LMArena German—1303
LMArena Japanese—1286
LMArena Korean—1314

Instruction Following o3-mini leads

GLM-4.5V: 69.2 (#175), o3-mini: 75.1 (#72)

BenchmarkGLM-4.5Vo3-mini
LMArena Instruction Following13111337
LiveBench Instruction Following—84.4%

Long Context GLM-4.5V leads

GLM-4.5V: 39.6 (#171), o3-mini: 33.8 (#256)

BenchmarkGLM-4.5Vo3-mini
LMArena Longer Query13041343
Fiction.LiveBench—50%

Writing & Preference GLM-4.5V leads

GLM-4.5V: 52.5 (#170), o3-mini: 50.3 (#182)

BenchmarkGLM-4.5Vo3-mini
LMArena Text13331337
LMArena Creative Writing12951286
LMArena Multi-Turn13321320
Short-Story Creative Writing—61.7%
LiveBench Language—50.7%

Frequently asked questions

Is GLM-4.5V better than o3-mini?

GLM-4.5V is the stronger model overall, scoring 39.8 to 36.7 on the Noometry Index.

Which is cheaper, GLM-4.5V or o3-mini?

GLM-4.5V is cheaper. It lists at $0.60 per million input tokens and $1.80 per million output tokens; o3-mini lists at $1.10 and $4.40.

Is GLM-4.5V or o3-mini better for coding?

o3-mini scores higher on coding benchmarks: 40.8 versus 39.5 in the Noometry coding category.

Which has the bigger context window?

o3-mini does, with 200K tokens against 64K.

How many benchmarks do GLM-4.5V and o3-mini share?

13 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and o3-mini has 51.

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