+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
DeepSeek-V3 vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V3 offers 6.1K more tokens in context window than Phi-4-multimodal-instruct. Phi-4-multimodal-instruct is $1.22 cheaper per million tokens. Phi-4-multimodal-instruct supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
+
+
+
+
DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
+
+
+
+
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.
1 month newer
DeepSeek-V3
DeepSeek
2024-12-25
Phi-4-multimodal-instruct
Microsoft
2025-02-01
+
+
+
+
+
+
+
+
+
+
+
+
Pricing Comparison
Cost per million tokens (USD)
+
+
+
+
DeepSeek-V3
Input:$0.27
Output:$1.10
+
+
+
+
Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10($1.22 cheaper)
Performance Metrics
Context window and performance specifications
+
+
+
+
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
+
+
+
+
DeepSeek-V3
1 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
+
+
+
+
Phi-4-multimodal-instruct
+
+
+
+
DeepSeek-V3
Avg Score:0.0%
Providers:1
+
+
+
+
Phi-4-multimodal-instruct
Avg Score:0.0%
Providers:1