Measured on Composite
This model has not carried enough traffic on Composite yet to publish a success rate, a latency figure or a traffic rank. The numbers appear here once it has.
AI model
Qwen: Qwen3.5 Plus 2026-02-15
qwen/qwen3.5-plus-02-15
Qwen: Qwen3.5 Plus 2026-02-15 is a 1,000,000-token model served on Composite at $0.325 per million tokens in and $1.95 per million tokens out.
Try in PlaygroundSpecifications
| Model ID | qwen/qwen3.5-plus-02-15 |
|---|---|
| Provider | cv11 |
| Context window | 1,000,000 tokens |
| Accepts | text, image, video |
| Returns | text |
| Input price | $0.325 per million tokens |
| Output price | $1.95 per million tokens |
| Prompt caching | Not offered for this model |
| Moderated | No |
| Cost on a monthly plan | About 3.6 plan credits per typical call (8k in, 1k out) |
| Routing endpoints | 2 (base plus 1 routing variant) |
Routing variants
The same model behind 1 alternative endpoint. Call the id directly to pin a route; the base id above picks for you.
| Route | Model ID | Provider | Price |
|---|---|---|---|
| cheapThink | qwen/qwen3.5-plus-02-15:cheapThink |
cv11 | $0.325 per million tokens input · $1.95 per million tokens output |
Pricing
$0.325 per million tokens input · $1.95 per million tokens output
Credits pay the provider’s price plus 25%; cache hits cost less.
On a monthly plan, a typical call (8k tokens in, 1k out) uses about 3.6 plan credits, at the provider's own price.
Provider
cv11
Roleplay fit
Qwen models pair large context windows with solid multilingual ability, useful for roleplay that switches languages or references long lore documents.
Context behavior
With a 1,000,000-token context window, it can hold a long-running roleplay or a full lorebook in memory without losing earlier plot details, so it suits multi-session campaigns and character cards with heavy backstory.
Cost for regular use
It is priced low enough for high-volume daily roleplay without the per-message cost adding up quickly.
From the provider
The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In a variety of...
Supplied by cv11, not written by Composite.
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