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DeepSeek-R1 vs Qwen3-235B-A22B-Thinking-2507
Comprehensive side-by-side LLM comparison
Qwen3-235B-A22B-Thinking-2507 offers 124.9K more tokens in context window than DeepSeek-R1. DeepSeek-R1 is $0.56 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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Alibaba Cloud / Qwen Team
Qwen3 235B Thinking was developed as a reasoning-enhanced variant, designed to incorporate extended thinking capabilities into the large-scale Qwen3 architecture. Built to combine deliberate analytical processing with mixture-of-experts efficiency, it serves tasks requiring both deep reasoning and computational practicality.
6 months newer
DeepSeek-R1
DeepSeek
2025-01-20
Qwen3-235B-A22B-Thinking-2507
Alibaba Cloud / Qwen Team
2025-07-25
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-R1
Input:$0.55
Output:$2.19($0.56 cheaper)
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Qwen3-235B-A22B-Thinking-2507
Input:$0.30
Output:$3.00
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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Qwen3-235B-A22B-Thinking-2507
Avg Score:0.0%
Providers:1