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DeepSeek R1 Distill Llama 70B vs Phi-3.5-vision-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-vision-instruct leads with 23.9% higher average benchmark score. Phi-3.5-vision-instruct supports multimodal inputs. Overall, Phi-3.5-vision-instruct is the stronger choice for coding tasks.
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DeepSeek
DeepSeek R1 Distill Llama 70B is a language model developed by DeepSeek. It achieves strong performance with an average score of 76.0% across 4 benchmarks. It excels particularly in MATH-500 (94.5%), AIME 2024 (86.7%), GPQA (65.2%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek'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.
5 months newer
Phi-3.5-vision-instruct
Microsoft
2024-08-23
DeepSeek R1 Distill Llama 70B
DeepSeek
2025-01-20
Performance Metrics
Context window and performance specifications
Average performance across 13 common benchmarks
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DeepSeek R1 Distill Llama 70B
Average Score:23.4%
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Phi-3.5-vision-instruct
Average Score:47.3%(+23.9%)
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek R1 Distill Llama 70B
1 providers
DeepInfra
Throughput: 37 tok/s
Latency: 0.65ms
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Phi-3.5-vision-instruct
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DeepSeek R1 Distill Llama 70B
Avg Score:23.4%
Providers:1
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Phi-3.5-vision-instruct
Avg Score:47.3%(+23.9%)
Providers:0