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GLM-4.5V vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-mini-instruct offers 59.4K more tokens in context window than GLM-4.5V. Phi-3.5-mini-instruct is $2.60 cheaper per million tokens. GLM-4.5V supports multimodal inputs. 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-3.5 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
11 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
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-3.5-mini-instruct
Input:$0.10
Output:$0.10($2.60 cheaper)
Performance Metrics
Context window and performance specifications
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-3.5-mini-instruct
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GLM-4.5V
Avg Score:0.0%
Providers:2
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Phi-3.5-mini-instruct
Avg Score:0.0%
Providers:1