qwen3.8-flash-next
Alibaba (Qwen)/Proprietary/1 provider
Qwen3.8 Flash Next is a fast, efficiency optimized model from Qwen with a 256K token context window. It supports vision input, reasoning, and strong function calling with tool choice, making it well suited for high throughput coding assistants and agentic workflows where speed and cost matter.MoreLess
Which id to call
tensorx/qwen3.8-flash-nextThis model has no managed policy yet, so call the provider endpoint directly. Every id in the endpoints table works the same way.
From /1M input
$0.20
TensorX Ltd.
Context
262K
262K output
Endpoints
1
1 region
Regions
1
chat
Capabilities 5/8
1 endpoint / 1 region
Providers serving qwen3.8-flash-next
Provider prices, per 1M tokens. Pay as you go adds 5%, or 0% on your own keys.
| Rank | Privacy | ||||||
|---|---|---|---|---|---|---|---|
| 1 |  TensorX Ltd. | EU | 262K | $0.20 | $0.50 | $0.05 | zdr |
A column is blank where no qualifying sample exists, and every row links to that provider's endpoint page.
model=
Which id to call
One base url, https://router.requesty.ai/v1, and one key for every id here.
tensorx/qwen3.8-flash-nextThis model has no managed policy yet, so call the provider endpoint directly. Every id in the endpoints table works the same way.
OpenAI compatible
Call it in three lines
Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.
123456789101112131415from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="tensorx/qwen3.8-flash-next", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)
Artificial Analysis
Benchmark scores
Artificial Analysis Coding Index: a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.
Graduate-level physics, chemistry & biology questions designed to resist Googling.
Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.
Scores from artificialanalysis.ai. They measure the model, not the provider, so they are the same on every endpoint above.
6
More from Alibaba (Qwen)
Reference
qwen3.8-flash-next questions
Which providers serve qwen3.8-flash-next?
qwen3.8-flash-next is available from 1 provider through Requesty: TensorX Ltd.. All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.
How much does qwen3.8-flash-next cost?
Pricing starts at $0.20 per million input tokens and $0.50 per million output tokens on TensorX Ltd., the cheapest endpoint. Prices vary by provider and region; the table above shows every endpoint. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.
Is qwen3.8-flash-next open weights?
No. qwen3.8-flash-next is a proprietary model from Alibaba (Qwen), served through Alibaba (Qwen)'s own API and licensed cloud platforms.
What is the context window of qwen3.8-flash-next?
qwen3.8-flash-next supports up to 262K tokens of context, with up to 262K output tokens per response. Some providers expose a smaller window; check the per-endpoint context column above.
How do I use qwen3.8-flash-next with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "tensorx/qwen3.8-flash-next" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.
Route qwen3.8-flash-next through one endpoint
One key for 1 provider on this model and 600+ others. No markup on provider prices, automatic failover, caching built in.