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DeepSeek-R1 vs Qwen3 235B A22B
Comprehensive side-by-side LLM comparison
DeepSeek-R1 offers 6.1K more tokens in context window than Qwen3 235B A22B. Qwen3 235B A22B is $2.54 cheaper per million tokens. 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 was developed as a large-scale model with 235 billion total parameters using a mixture-of-experts architecture activating 22 billion parameters. Built to provide frontier capabilities with computational efficiency through sparse activation, it represents Qwen's advancement into very large-scale model development.
3 months newer
DeepSeek-R1
DeepSeek
2025-01-20
Qwen3 235B A22B
Alibaba Cloud / Qwen Team
2025-04-29
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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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Qwen3 235B A22B
Input:$0.10
Output:$0.10($2.54 cheaper)
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
Avg Score:0.0%
Providers:4