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DeepSeek-V2.5 vs QwQ-32B-Preview
Comprehensive side-by-side LLM comparison
QwQ-32B-Preview offers 49.2K more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V2.5 was developed as an enhanced iteration of the DeepSeek-V2 architecture, designed to incorporate improvements in model quality and efficiency. Built to advance the DeepSeek foundation model series, it provides refined capabilities for general-purpose language understanding and generation tasks.
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Alibaba Cloud / Qwen Team
QwQ 32B Preview was introduced as an early access version of the QwQ reasoning model, designed to allow researchers and developers to experiment with advanced analytical capabilities. Built to gather feedback on reasoning-enhanced architecture, it represents an experimental step toward more thoughtful language models.
6 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
QwQ-32B-Preview
Alibaba Cloud / Qwen Team
2024-11-28
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V2.5
Input:$0.14
Output:$0.28
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QwQ-32B-Preview
Input:$0.15
Output:$0.20($0.07 cheaper)
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
QwQ-32B-Preview
2024-11-28
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-V2.5
3 providers
DeepInfra
Throughput: 63 tok/s
Latency: 0.5ms
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
Hyperbolic
Throughput: 100 tok/s
Latency: 0.5ms
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DeepSeek-V2.5
Avg Score:0.0%
Providers:3
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QwQ-32B-Preview
Avg Score:0.0%
Providers:4