Allocate
Qwen3.8-2.4T-A95B
APINew- Price first checked
- Listed on Allocate
Qwen3.8-2.4T-A95B is a language model from Qwen with a 1M-token context window. Provider list price is $2 per million input tokens and $6 per million output; on Allocate you pay $2.14 and $6.42. It is a closed model served over API; the weights are not published.
What a real workload costs
Take 1,000,000 requests a month at 1,200 input and 350 output tokens each: 1,200M input and 350M output tokens. At list prices that is 1,200 × $2 + 350 × $6 = $4,500 a month. Billed on Allocate it is $4,815.
Example usage
curl https://api.allocate.network/v1/chat/completions \
-H "Authorization: Bearer $ALLOCATE_KEY" \
-d '{
"model": "qwen/qwen3.8-2.4t-a95b",
"messages": [{ "role": "user", "content": "Summarise the attached contract." }]
}'Common questions
How much does Qwen3.8-2.4T-A95B cost per million tokens?
Provider list price is $2 per million input tokens and $6 per million output tokens. On Allocate you pay $2.14 in and $6.42 out.
What context window does Qwen3.8-2.4T-A95B have?
1,010,000 tokens (1M). At roughly 0.75 words per token, that is about 758k words of English text per request.
What does cached input cost on Qwen3.8-2.4T-A95B?
$0.25 per million tokens at list ($0.27 billed). Repeated prompt prefixes, such as a stable system prompt or tool definitions, bill at this rate instead of the full input price.
Can I fine-tune Qwen3.8-2.4T-A95B?
No. Qwen3.8-2.4T-A95B is a closed model served over API; the weights are not published. If you want a model you can train and own, start from an open-weights base in the catalog and fine-tune that.
Has the price of Qwen3.8-2.4T-A95B changed?
Allocate has checked the provider list price hourly since 12 Sep 2026. It has not changed in that time. The price history chart on this page shows every change.
How do I call Qwen3.8-2.4T-A95B on Allocate?
Send qwen/qwen3.8-2.4t-a95b in the model field of the OpenAI-compatible endpoint at api.allocate.network/v1, or point a route name (like prod/support-agent) at it so you can swap the model later without a deploy.