Model Comparison

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

GLM-4.5V

Zhipu AI

GLM-4.5V is a multimodal language model developed by Zhipu AI. It supports a 197K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. 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.

Microsoft

Phi-4-multimodal-instruct

Microsoft

Phi-4-multimodal-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 72.0% across 15 benchmarks. It excels particularly in ScienceQA Visual (97.5%), DocVQA (93.2%), MMBench (86.7%). The model shows particular specialization in general tasks with an average performance of 75.8%. It supports a 256K 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. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.

Microsoft

Phi-4-multimodal-instruct

Microsoft

2025-02-01

GLM-4.5V

Zhipu AI

2025-08-11

6 months newer

Pricing Comparison

Cost per million tokens (USD)

GLM-4.5V

Input:$0.60
Output:$2.20
Microsoft

Phi-4-multimodal-instruct

$2.65 cheaper
Input:$0.05
Output:$0.10

Performance Metrics

Context window and performance specifications

GLM-4.5V

Max Context:196.6K
Parameters:108.0B
Microsoft

Phi-4-multimodal-instruct

Larger context
Max Context:256.0K
Parameters:5.6B

Average performance across 15 common benchmarks

GLM-4.5V

Average Score:0.0%
Microsoft

Phi-4-multimodal-instruct

+72.0%
Average Score:72.0%
Knowledge Cutoff
Training data recency comparison

Phi-4-multimodal-instruct

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

GLM-4.5V

2 providers

Novita

ZeroEval

Throughput: 85 tok/s
Latency: 0.7ms
Microsoft

Phi-4-multimodal-instruct

1 providers

DeepInfra

Throughput: 25 tok/s
Latency: 0.5ms

GLM-4.5V

Avg Score:0.0%
Providers:2
Microsoft

Phi-4-multimodal-instruct

+72.0%
Avg Score:72.0%
Providers:1