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DeepSeek-R1 vs Kimi K2 Base
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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Moonshot AI
Kimi K2 Base was created as the foundation model in the K2 series, designed to serve as a starting point for fine-tuning and customization. Built to provide strong base capabilities for domain-specific applications, it enables developers to build specialized solutions on Moonshot's architecture.
5 months newer
DeepSeek-R1
DeepSeek
2025-01-20
Kimi K2 Base
Moonshot AI
2025-07-11
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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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Kimi K2 Base
Avg Score:0.0%
Providers:0