Qwen3 235B A22B Instruct 2507 vs Qwen3.5-Flash
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 Qwen3 235B A22B Instruct 2507 and Qwen3.5-Flash.
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,...
Qwen3.5-Flash
The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the...
Technical Specifications
| Specification | Qwen3 235B A22B Instruct 2507 | Qwen3.5-Flash |
|---|---|---|
| Provider | Alibaba | Alibaba |
| Context Window | 262,144 tokens | 1,000,000 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 | beta |
| API Available | Yes | Yes |
| Released Date | 2025-07-21 | 2026-02-25 |
API Pricing Comparison
Input Price per Million Tokens
Qwen3 235B A22B Instruct 2507
$0.09
Qwen3.5-Flash
$0.07
Output Price per Million Tokens
Qwen3 235B A22B Instruct 2507
$0.10
Qwen3.5-Flash
$0.26
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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.
Qwen3 235B A22B Instruct 2507 Quirks & Gotchas
No developer gotchas reported.
Qwen3.5-Flash Quirks & Gotchas
No developer gotchas reported.