DeepSeek V4 Pro vs Qwen3 Coder Next
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 Coder Next.
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 Coder Next
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...
Technical Specifications
| Specification | DeepSeek V4 Pro | Qwen3 Coder Next |
|---|---|---|
| Provider | DeepSeek | Alibaba |
| Context Window | 1,048,576 tokens | 262,144 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 | 2026-02-04 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V4 Pro
$0.43
Qwen3 Coder Next
$0.11
Output Price per Million Tokens
DeepSeek V4 Pro
$0.87
Qwen3 Coder Next
$0.80
Want to test both models live?
Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.
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
- โธMoE architecture โ cold-start latency on first request, use keep-alive
- โธBest cost-performance ratio of any frontier model โ strong tool calling for agentic use
Qwen3 Coder Next Quirks & Gotchas
No developer gotchas reported.