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DeepSeek-R1 vs Phi-3.5-vision-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-vision-instruct supports multimodal inputs. DeepSeek-R1 is available on 5 providers. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-R1 was developed as a reasoning-focused language model, designed to combine chain-of-thought reasoning with reinforcement learning techniques. Built to excel at complex problem-solving through trial-and-error learning and deliberate analytical processes, it demonstrates the power of efficient training methods in open-source model development.
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Microsoft
Phi-3.5 Vision was developed as a multimodal variant of Phi-3.5, designed to understand and reason about both images and text. Built to extend the Phi family's efficiency into vision-language tasks, it enables compact multimodal AI for practical applications.
5 months newer
Phi-3.5-vision-instruct
Microsoft
2024-08-23
DeepSeek-R1
DeepSeek
2025-01-20
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Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-R1
5 providers
DeepInfra
Throughput: 0.9 tok/s
Latency: 0.3ms
DeepSeek
Throughput: 9 tok/s
Latency: 0.3ms
Fireworks
Throughput: 2.1 tok/s
Latency: 0.3ms
Together
Throughput: 4 tok/s
Latency: 0.6ms
ZeroEval
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DeepSeek-R1
Avg Score:0.0%
Providers:5
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Phi-3.5-vision-instruct
Avg Score:0.0%
Providers:0