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Model Comparison

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

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.

OpenAI

o4-mini

OpenAI

o4-mini is a multimodal language model developed by OpenAI. It achieves strong performance with an average score of 66.5% across 14 benchmarks. It excels particularly in AIME 2024 (93.4%), AIME 2025 (92.7%), MathVista (84.3%). The model shows particular specialization in math tasks with an average performance of 88.5%. It supports a 300K token context window for handling large documents. 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 2025, it represents OpenAI's latest advancement in AI technology.

OpenAI

o4-mini

OpenAI

2025-04-16

GLM-4.5

Zhipu AI

2025-07-28

3 months newer

Pricing Comparison

Cost per million tokens (USD)

GLM-4.5

$3.50 cheaper
Input:$0.40
Output:$1.60
OpenAI

o4-mini

Input:$1.10
Output:$4.40

Performance Metrics

Context window and performance specifications

GLM-4.5

Max Context:262.1K
Parameters:355.0B
OpenAI

o4-mini

Larger context
Max Context:300.0K

Average performance across 6 common benchmarks

GLM-4.5

Average Score:66.8%
OpenAI

o4-mini

+2.4%
Average Score:69.2%

Performance comparison across key benchmark categories

GLM-4.5

math
+9.7%
98.2%
general
+17.8%
79.3%
code
50.7%
agents
55.5%
OpenAI

o4-mini

math
88.5%
general
61.5%
code
+18.2%
68.9%
agents
+2.0%
57.5%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

o4-mini

2024-05-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

GLM-4.5

1 providers

DeepInfra

OpenAI

o4-mini

1 providers

OpenAI

Throughput: 115 tok/s
Latency: 5.2ms

GLM-4.5

Avg Score:66.8%
Providers:1
OpenAI

o4-mini

+2.4%
Avg Score:69.2%
Providers:1