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Mistral Small 3.1 24B Base vs Phi-3.5-vision-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-vision-instruct leads with 23.1% higher average benchmark score. Overall, Phi-3.5-vision-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-3.5-vision-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 68.3% across 9 benchmarks. It excels particularly in ScienceQA (91.3%), POPE (86.1%), MMBench (81.9%). 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 Microsoft's latest advancement in AI technology.
6 months newer
Phi-3.5-vision-instruct
Microsoft
2024-08-23
Mistral Small 3.1 24B Base
Mistral AI
2025-03-17
Performance Metrics
Context window and performance specifications
Average performance across 13 common benchmarks
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Mistral Small 3.1 24B Base
Average Score:24.2%
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Phi-3.5-vision-instruct
Average Score:47.3%(+23.1%)
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-3.5-vision-instruct
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Mistral Small 3.1 24B Base
Avg Score:24.2%
Providers:1
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Phi-3.5-vision-instruct
Avg Score:47.3%(+23.1%)
Providers:0