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DeepSeek-R1 vs GPT-3.5 Turbo
Comprehensive side-by-side LLM comparison
DeepSeek-R1 offers 241.7K more tokens in context window than GPT-3.5 Turbo. GPT-3.5 Turbo is $0.74 cheaper per million tokens. 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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OpenAI
GPT-3.5 Turbo was developed as an optimized version of GPT-3.5, designed to provide a balance of capability and efficiency for conversational and completion tasks. Built to serve as a cost-effective option for applications requiring reliable language understanding and generation, it became widely adopted for chatbots, content generation, and general-purpose AI assistance.
1 year newer
GPT-3.5 Turbo
OpenAI
2023-03-21
DeepSeek-R1
DeepSeek
2025-01-20
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-R1
Input:$0.55
Output:$2.19
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GPT-3.5 Turbo
Input:$0.50
Output:$1.50($0.74 cheaper)
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
GPT-3.5 Turbo
2021-09-30
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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GPT-3.5 Turbo
Avg Score:0.0%
Providers:2