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DeepSeek VL2 vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
DeepSeek VL2 offers 2.6K more tokens in context window than Phi-3.5-mini-instruct. Phi-3.5-mini-instruct is $4809.30 cheaper per million tokens. DeepSeek VL2 supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-VL2 was developed as a vision-language model, designed to handle both visual and textual inputs for multimodal understanding tasks. Built to extend DeepSeek's capabilities beyond text-only processing, it enables applications requiring integrated analysis of images and language.
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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.
3 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
DeepSeek VL2
DeepSeek
2024-12-13
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek VL2
Input:$9.50
Output:$4800.00
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($4809.30 cheaper)
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek VL2
1 providers
Replicate
Throughput: 22 tok/s
Latency: 0.5ms
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Phi-3.5-mini-instruct
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DeepSeek VL2
Avg Score:0.0%
Providers:1
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Phi-3.5-mini-instruct
Avg Score:0.0%
Providers:1