Model comparison

Gemini 1.5 Flash (May 2024) vs GLM-4.5V

GLM-4.5V is the stronger model overall, scoring 39.2 to 32.9 on the Noometry Index.

Last verified . 14 shared benchmarks.

Gemini 1.5 Flash (May 2024) Google

32.9

Rank #240 Confirmed

GLM-4.5V Z.ai (Zhipu)

39.2

Rank #158 Confirmed

Summary

  • They share 14 benchmarks with published results for both. Gemini 1.5 Flash (May 2024) scores higher in 1 category and GLM-4.5V in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-4.5V leads 34.7 to 20.8.
  • GLM-4.5V has downloadable open weights; the other is API-only.

Side by side

Gemini 1.5 Flash (May 2024) and GLM-4.5V specifications
Gemini 1.5 Flash (May 2024)GLM-4.5V
ProviderGoogleZ.ai (Zhipu)
Noometry Index32.939.2
Released2024-05-142025-08-11
WeightsProprietaryOpen
Context window—64K
Max output—16K
Input $ / M tokens—$0.60
Output $ / M tokens—$1.80
Results tracked4215

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Category by category

Coding GLM-4.5V leads

Gemini 1.5 Flash (May 2024): 33.9 (#233), GLM-4.5V: 38.9 (#152)

Coding benchmarks
BenchmarkGemini 1.5 Flash (May 2024)GLM-4.5V
LMArena Coding12621347
WeirdML24.9%—
BigCodeBench Instruct43.5%—
BigCodeBench Complete55.1%—
HumanEval+75.6%—
MBPP+67.5%—

Agentic & Tool Use Not comparable

Gemini 1.5 Flash (May 2024): 26.3 (#97), GLM-4.5V: —

Agentic & Tool Use benchmarks
BenchmarkGemini 1.5 Flash (May 2024)GLM-4.5V
BALROG14.6%—

Reasoning GLM-4.5V leads

Gemini 1.5 Flash (May 2024): 20.8 (#212), GLM-4.5V: 26.5 (#118)

Reasoning benchmarks
BenchmarkGemini 1.5 Flash (May 2024)GLM-4.5V
LMArena Hard Prompts12571335
Kagi LLM Benchmark—59.8%
DTBench53.8%—
Epoch Capabilities Index129.37—
ForecastBench53.9—
PIQA87.5%—

Math GLM-4.5V leads

Gemini 1.5 Flash (May 2024): 20.8 (#274), GLM-4.5V: 34.7 (#157)

Math benchmarks
BenchmarkGemini 1.5 Flash (May 2024)GLM-4.5V
LMArena Math12691353
OTIS Mock AIME 2024-202516.3%—
Omni-MATH30.4%—
MATH Level 561.9%—
FrontierMath (Feb 2025 set)0%—
GSM8K82.4%—

Knowledge GLM-4.5V leads

Gemini 1.5 Flash (May 2024): 26.2 (#253), GLM-4.5V: 36.8 (#155)

Knowledge benchmarks
BenchmarkGemini 1.5 Flash (May 2024)GLM-4.5V
LMArena Expert12331353
GPQA Diamond47.3%—
MMLU-Pro67.8%—
GPQA (HELM)43.7%—
BoolQ85.8%—
MMLU77.9%—

Multimodal Gemini 1.5 Flash (May 2024) leads

Gemini 1.5 Flash (May 2024): 35.3 (#76), GLM-4.5V: 33.6 (#86)

Multimodal benchmarks
BenchmarkGemini 1.5 Flash (May 2024)GLM-4.5V
LMArena Vision11411154
Video-MME70.3%—
GeoBench76%—

Multilingual GLM-4.5V leads

Gemini 1.5 Flash (May 2024): 43.1 (#184), GLM-4.5V: 44.9 (#172)

Multilingual benchmarks
BenchmarkGemini 1.5 Flash (May 2024)GLM-4.5V
LMArena Non-English12781304
LMArena Chinese12951338
LMArena Russian12881299
LMArena Spanish12421335
LMArena French1257—
LMArena German1262—
LMArena Japanese1252—
LMArena Korean1220—

Instruction Following GLM-4.5V leads

Gemini 1.5 Flash (May 2024): 67.0 (#199), GLM-4.5V: 69.4 (#170)

Instruction Following benchmarks
BenchmarkGemini 1.5 Flash (May 2024)GLM-4.5V
LMArena Instruction Following12581311
IFEval83.1%—

Long Context Too close to call

Gemini 1.5 Flash (May 2024): 39.0 (#182), GLM-4.5V: 39.6 (#166)

Long Context benchmarks
BenchmarkGemini 1.5 Flash (May 2024)GLM-4.5V
LMArena Longer Query12841305

Writing & Preference GLM-4.5V leads

Gemini 1.5 Flash (May 2024): 48.9 (#190), GLM-4.5V: 52.7 (#162)

Writing & Preference benchmarks
BenchmarkGemini 1.5 Flash (May 2024)GLM-4.5V
LMArena Text12871333
LMArena Creative Writing12851295
LMArena Multi-Turn12531333
WildBench79.2%—

Frequently asked questions

Is Gemini 1.5 Flash (May 2024) better than GLM-4.5V?

GLM-4.5V is the stronger model overall, scoring 39.2 to 32.9 on the Noometry Index.

Is Gemini 1.5 Flash (May 2024) or GLM-4.5V better for coding?

GLM-4.5V scores higher on coding benchmarks: 38.9 versus 33.9 in the Noometry coding category.

How many benchmarks do Gemini 1.5 Flash (May 2024) and GLM-4.5V share?

14 benchmarks have published results for both models. Gemini 1.5 Flash (May 2024) has 42 scored results on Noometry and GLM-4.5V has 15.

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