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DeepSeek VL2 Tiny vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-mini-instruct leads with 20.8% higher average benchmark score. DeepSeek VL2 Tiny supports multimodal inputs. Overall, Phi-3.5-mini-instruct is the stronger choice for coding tasks.
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DeepSeek
DeepSeek VL2 Tiny is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 63.1% across 14 benchmarks. It excels particularly in DocVQA (88.9%), ChartQA (81.0%), OCRBench (80.9%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
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Microsoft
Phi-3.5-mini-instruct is a language model developed by Microsoft. The model shows competitive results across 31 benchmarks. It excels particularly in GSM8k (86.2%), ARC-C (84.6%), RULER (84.1%). 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 2024, it represents Microsoft's latest advancement in AI technology.
3 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
DeepSeek VL2 Tiny
DeepSeek
2024-12-13
Performance Metrics
Context window and performance specifications
Average performance across 45 common benchmarks
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DeepSeek VL2 Tiny
Average Score:19.6%
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Phi-3.5-mini-instruct
Average Score:40.4%(+20.8%)
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek VL2 Tiny
0 providers
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Phi-3.5-mini-instruct
1 providers
Azure
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DeepSeek VL2 Tiny
Avg Score:19.6%
Providers:0
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Phi-3.5-mini-instruct
Avg Score:40.4%(+20.8%)
Providers:1