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Mistral Small 3.1 24B Base vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 40.3% higher average benchmark score. Both models have similar pricing. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
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Mistral AI
Mistral Small 3.1 24B Base is a multimodal language model developed by Mistral AI. It achieves strong performance with an average score of 62.9% across 5 benchmarks. It excels particularly in MMLU (81.0%), TriviaQA (80.5%), MMMU (59.3%). 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 Mistral AI'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.
1 month newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Mistral Small 3.1 24B Base
Mistral AI
2025-03-17
Pricing Comparison
Cost per million tokens (USD)
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Mistral Small 3.1 24B Base
Input:$0.10
Output:$0.30
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10($0.25 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 19 common benchmarks
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Mistral Small 3.1 24B Base
Average Score:16.5%
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Phi-4-multimodal-instruct
Average Score:56.9%(+40.3%)
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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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Mistral Small 3.1 24B Base
1 providers
Mistral AI
Throughput: 137.1 tok/s
Latency: 0.23ms
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Phi-4-multimodal-instruct
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Mistral Small 3.1 24B Base
Avg Score:16.5%
Providers:1
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Phi-4-multimodal-instruct
Avg Score:56.9%(+40.3%)
Providers:1