DeepSeek V3.1 vs Qwen3 235B A22B Instruct 2507
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 235B A22B Instruct 2507.
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 235B A22B Instruct 2507
Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...
Technical Specifications
| Specification | DeepSeek V3.1 | Qwen3 235B A22B Instruct 2507 |
|---|---|---|
| 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 | 2025-07-21 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V3.1
$0.21
Qwen3 235B A22B Instruct 2507
$0.09
Output Price per Million Tokens
DeepSeek V3.1
$0.79
Qwen3 235B A22B Instruct 2507
$0.10
Want to test both models live?
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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 V3.1 Quirks & Gotchas
No developer gotchas reported.
Qwen3 235B A22B Instruct 2507 Quirks & Gotchas
No developer gotchas reported.