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Grok-1.5V vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 2.6% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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xAI
Grok 1.5V was introduced as a vision-enabled variant of Grok 1.5, designed to understand and reason about both images and text. Built to extend Grok's capabilities into multimodal applications, it enables visual question answering and image analysis alongside textual understanding.
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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.
9 months newer
Grok-1.5V
xAI
2024-04-12
Phi-4-multimodal-instruct
Microsoft
2025-02-01
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Performance Metrics
Context window and performance specifications
Average performance across 6 common benchmarks
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Grok-1.5V
Average Score:72.4%
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Phi-4-multimodal-instruct
Average Score:75.0%(+2.6%)
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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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Grok-1.5V
0 providers
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Phi-4-multimodal-instruct
1 providers
DeepInfra
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Grok-1.5V
Avg Score:72.4%
Providers:0
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Phi-4-multimodal-instruct
Avg Score:75.0%(+2.6%)
Providers:1