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DeepSeek-R1 vs Phi 4 Mini
Comprehensive side-by-side LLM comparison
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-4 Mini was created as an even more compact variant of Phi-4, designed to bring fourth-generation capabilities to the smallest possible footprint. Built for extreme efficiency scenarios, it enables AI capabilities on devices and applications where resources are severely constrained.
12 days newer
DeepSeek-R1
DeepSeek
2025-01-20
Phi 4 Mini
Microsoft
2025-02-01
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Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
Phi 4 Mini
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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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 4 Mini
Avg Score:0.0%
Providers:0