+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
DeepSeek-V2.5 vs Qwen3 235B A22B
Comprehensive side-by-side LLM comparison
Qwen3 235B A22B leads with 2.9% higher average benchmark score. Qwen3 235B A22B 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.
+
+
+
+
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.
+
+
+
+
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.
11 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Qwen3 235B A22B
Alibaba Cloud / Qwen Team
2025-04-29
+
+
+
+
+
+
+
+
+
+
+
+
Pricing Comparison
Cost per million tokens (USD)
+
+
+
+
DeepSeek-V2.5
Input:$0.14
Output:$0.28
+
+
+
+
Qwen3 235B A22B
Input:$0.10
Output:$0.10($0.22 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 6 common benchmarks
+
+
+
+
DeepSeek-V2.5
Average Score:80.5%
+
+
+
+
Qwen3 235B A22B
Average Score:83.4%(+2.9%)
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
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
+
+
+
+
+
+
+
DeepSeek-V2.5
Avg Score:80.5%
Providers:3
+
+
+
+
Qwen3 235B A22B
Avg Score:83.4%(+2.9%)
Providers:4