🚀 Website under development • Launching soon

Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Google

Gemini 1.5 Pro

Google

Gemini 1.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 72.6% across 23 benchmarks. It excels particularly in XSTest (98.8%), HellaSwag (93.3%), GSM8k (90.8%). With a 2.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Google's latest advancement in AI technology.

GLM-4.5

Zhipu AI

GLM-4.5 is a language model developed by Zhipu AI. It achieves strong performance with an average score of 64.0% across 14 benchmarks. It excels particularly in MATH-500 (98.2%), AIME 2024 (91.0%), MMLU-Pro (84.6%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Zhipu AI's latest advancement in AI technology.

Google

Gemini 1.5 Pro

Google

2024-05-01

GLM-4.5

Zhipu AI

2025-07-28

1 year newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 1.5 Pro

Input:$2.50
Output:$10.00

GLM-4.5

$10.50 cheaper
Input:$0.40
Output:$1.60

Performance Metrics

Context window and performance specifications

Google

Gemini 1.5 Pro

Larger context
Max Context:2.1M

GLM-4.5

Max Context:262.1K
Parameters:355.0B

Average performance across 2 common benchmarks

Google

Gemini 1.5 Pro

Average Score:67.5%

GLM-4.5

+14.4%
Average Score:81.8%

Performance comparison across key benchmark categories

Google

Gemini 1.5 Pro

math
74.9%
reasoning
+52.3%
93.3%
general
68.9%
code
+23.8%
74.5%

GLM-4.5

math
+23.3%
98.2%
reasoning
41.1%
general
+10.4%
79.3%
code
50.7%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 1.5 Pro

2023-11-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 1.5 Pro

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms

GLM-4.5

1 providers

DeepInfra

Google

Gemini 1.5 Pro

Avg Score:67.5%
Providers:1

GLM-4.5

+14.4%
Avg Score:81.8%
Providers:1