DeepSeek V3.1 vs Qwen3.5-27B
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 V3.1 and Qwen3.5-27B.
DeepSeek V3.1
DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...
Qwen3.5-27B
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of...
Technical Specifications
| Specification | DeepSeek V3.1 | Qwen3.5-27B |
|---|---|---|
| Provider | DeepSeek | Alibaba |
| Context Window | 163,840 tokens | 262,144 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | self hostable | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-08-21 | 2026-02-25 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V3.1
$0.21
Qwen3.5-27B
$0.20
Output Price per Million Tokens
DeepSeek V3.1
$0.79
Qwen3.5-27B
$1.56
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 V3.1 Quirks & Gotchas
No developer gotchas reported.
Qwen3.5-27B Quirks & Gotchas
No developer gotchas reported.