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GLM-4.5V vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct offers 59.4K more tokens in context window than GLM-4.5V. Phi-4-multimodal-instruct is $2.65 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
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Zhipu AI
GLM-4.5V was developed as a vision-language variant, designed to understand and reason about both images and text in Chinese and English. Built to extend Zhipu AI's multilingual capabilities into multimodal applications, it enables visual understanding alongside bilingual language processing.
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Microsoft
Phi-4 Multimodal was created to handle multiple input modalities including text, images, and potentially other formats. Built to extend Phi-4's efficiency into multimodal applications, it demonstrates that compact models can successfully integrate diverse information types.
6 months newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
GLM-4.5V
Zhipu AI
2025-08-11
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Pricing Comparison
Cost per million tokens (USD)
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GLM-4.5V
Input:$0.60
Output:$2.20
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10($2.65 cheaper)
Performance Metrics
Context window and performance specifications
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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
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GLM-4.5V
2 providers
Novita
ZeroEval
Throughput: 85 tok/s
Latency: 0.7ms
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Phi-4-multimodal-instruct
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GLM-4.5V
Avg Score:0.0%
Providers:2
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Phi-4-multimodal-instruct
Avg Score:0.0%
Providers:1