DeepSeek V4 Pro vs Qwen2.5 72B Instruct
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for DeepSeek V4 Pro and Qwen2.5 72B Instruct.
DeepSeek V4 Pro
DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...
Qwen2.5 72B Instruct
Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...
Technical Specifications
| Specification | DeepSeek V4 Pro | Qwen2.5 72B Instruct |
|---|---|---|
| Provider | DeepSeek | Alibaba |
| Context Window | 1,048,576 tokens | 131,072 tokens |
| Agent Suitability | 94/100 | N/A |
| Time to First Token (TTFT) | 280 ms | N/A |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-24 | 2024-09-19 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V4 Pro
$0.43
Qwen2.5 72B Instruct
$0.36
Output Price per Million Tokens
DeepSeek V4 Pro
$0.87
Qwen2.5 72B Instruct
$0.40
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
DeepSeek V4 Pro Quirks & Gotchas
- ▸MoE architecture — cold-start latency on first request, use keep-alive
- ▸Best cost-performance ratio of any frontier model — strong tool calling for agentic use
Qwen2.5 72B Instruct Quirks & Gotchas
No developer gotchas reported.