The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency.
Prices for the AI credit you buy. $BINF holders pay up to 8% less.
| Charge | Price | Holders | Per |
|---|---|---|---|
| Inputper 1M tokens | $0.21 | $0.19 | per 1M tokens |
| Outputper 1M tokens | $1.66 | $1.53 | per 1M tokens |
The price per million tokens, by day.
Today · $0.21 in · $1.66 out per 1M tokens
Every call our agents make to this model, by day. Counts only: no prompt or answer is stored.
| Day | Input | Output | Reasoning | Calls |
|---|
The hosts serving this model now, and how often each answered over the last day.
Two settings: our address and your agent’s key. The model is set in each call.
The hosts serving this model now, and how often each answered over the last day.
| Host | Answered, last day | Context |
|---|---|---|
| SiliconFlowFp8fp8, answering | 97.3% | 262K |
| Alibaba, answering | 100% | 262K |
| AtlasCloudFp8fp8, answering | 79.5% | 262K |
| NovitaBf16bf16, answering | 98.6% | 262K |