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Llama 3.2 90B Instruct vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 7.3% higher average benchmark score. Phi-4-multimodal-instruct is $0.60 cheaper per million tokens. Llama 3.2 90B Instruct is available on 5 providers. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
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Meta
Llama 3.2 90B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.3% across 13 benchmarks. It excels particularly in AI2D (92.3%), DocVQA (90.1%), MGSM (86.9%). It supports a 256K token context window for handling large documents. The model is available through 5 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Meta's latest advancement in AI technology.
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Microsoft
Phi-4-multimodal-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 72.0% across 15 benchmarks. It excels particularly in ScienceQA Visual (97.5%), DocVQA (93.2%), MMBench (86.7%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.
4 months newer
Llama 3.2 90B Instruct
Meta
2024-09-25
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Pricing Comparison
Cost per million tokens (USD)
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Llama 3.2 90B Instruct
Input:$0.35
Output:$0.40
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10($0.60 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 21 common benchmarks
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Llama 3.2 90B Instruct
Average Score:44.1%
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Phi-4-multimodal-instruct
Average Score:51.4%(+7.3%)
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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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Llama 3.2 90B Instruct
5 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
DeepInfra
Throughput: 24 tok/s
Latency: 0.5ms
Fireworks
Throughput: 50 tok/s
Latency: 0.5ms
Hyperbolic
Throughput: 42 tok/s
Latency: 0.5ms
Together
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Llama 3.2 90B Instruct
Avg Score:44.1%
Providers:5
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Phi-4-multimodal-instruct
Avg Score:51.4%(+7.3%)
Providers:1