DeepSeek V4 Pro vs Qwen3.5 397B A17B
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 Qwen3.5 397B A17B.
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,...
Qwen3.5 397B A17B
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...
Technical Specifications
| Specification | DeepSeek V4 Pro | Qwen3.5 397B A17B |
|---|---|---|
| Provider | DeepSeek | Alibaba |
| Context Window | 1,048,576 tokens | 256,000 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 | 2026-02-16 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V4 Pro
$0.43
Qwen3.5 397B A17B
$0.39
Output Price per Million Tokens
DeepSeek V4 Pro
$0.87
Qwen3.5 397B A17B
$2.45
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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
Qwen3.5 397B A17B Quirks & Gotchas
No developer gotchas reported.