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DeepSeek-V2.5 vs Qwen3 32B
Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 2.2% higher average benchmark score. Qwen3 32B offers 239.6K 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
Qwen3 32B was developed as a dense 32-billion-parameter model in the Qwen3 family, designed to provide strong language understanding without mixture-of-experts complexity. Built for applications requiring straightforward deployment and reliable performance, it serves as a capable mid-to-large-scale foundation model.
11 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Qwen3 32B
Alibaba Cloud / Qwen Team
2025-04-29
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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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Qwen3 32B
Input:$0.10
Output:$0.30($0.02 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek-V2.5
Average Score:74.2%(+2.2%)
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Qwen3 32B
Average Score:72.0%
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:74.2%(+2.2%)
Providers:3
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Qwen3 32B
Avg Score:72.0%
Providers:3