Qwen: Qwen3.5-Flash Rank
Qwen3.5-Flash has an overall score of 82 out of 100, tied for rank 13 of 291. The published scores are price 89, context 70, and recency 88. The overall score is their average. parameters and freshness are not published and are left out of the average.
Data sourced from OpenRouter API and manual data collection | Last updated: Nov 3, 2026, 8:01 AM UTC
Component scores are ranked in
tied for rank 13 of 291
Component scores
| Score | Result | Published value | Source |
|---|---|---|---|
| Freshness | — | — | AI Knowledge Cutoff |
| Recency | 88 | AI Release Date | |
| Context | 70 | 1M tokens, output 65.5K | AI Context Window |
| Parameters | — | — | AI Parameter Count |
| Price | 89 | $0.114 / 1M blended, $0.065 / 1M input, $0.26 / 1M output | AI Token Price |
12 listed models have a higher overall score. Among Qwen models, it ranks 3 of 38.
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...
Higher overall scores
Other Qwen models
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Frequently asked questions
What is the Qwen3.5-Flash rank?
Qwen3.5-Flash has an overall score of 82 out of 100, tied for rank 13 of 291. The published scores are price 89, context 70, and recency 88. The overall score is their average. parameters and freshness are not published and are left out of the average.
Where does Qwen3.5-Flash rank?
Qwen3.5-Flash is tied for rank 13 of 291. 12 listed models have a higher overall score. Among Qwen models, it ranks 3 of 38.
What scores make up Qwen3.5-Flash?
Qwen3.5-Flash scores price 89 (AI Token Price), context 70 (AI Context Window), and recency 88 (AI Release Date). The overall score of 82 is the average of those 3.