Vision-language model with hybrid linear-attention plus sparse MoE, 1M context, and fast multimodal text/image/video inference.
Alibaba CloudText Generation1M contextReleased Feb 24, 2026SingaporeProprietary EndpointVision-language model with hybrid linear-attention plus sparse MoE, 1M context, and fast multimodal text/image/video inference.
Also known as Alibaba Cloud Qwen3.5 Flash, Qwen3.5-Flash, qwen3-5-flash
qwen3-5-flash/v1/chat/completionsPOST/v1/responsesPOST/v1/messagesPOST/v1beta/models/qwen3-5-flash:generateContentqwen3.5-flashLive pay-as-you-go rates from the EmpirioLabs catalog. You are billed only for what you use, with no monthly minimum.
Qwen3.5 Flash serves the OpenAI-compatible Chat Completions API. Point any OpenAI SDK at https://api.empiriolabs.ai/v1 with your EmpirioLabs API key and use the model id qwen3-5-flash. Get an API key from the EmpirioLabs dashboard.
curl https://api.empiriolabs.ai/v1/chat/completions \
-H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-5-flash",
"messages": [
{"role": "user", "content": "Write a haiku about the ocean."}
]
}'from openai import OpenAI
client = OpenAI(
base_url="https://api.empiriolabs.ai/v1",
api_key="YOUR_EMPIRIOLABS_API_KEY",
)
response = client.chat.completions.create(
model="qwen3-5-flash",
messages=[{"role": "user", "content": "Write a haiku about the ocean."}],
)
print(response.choices[0].message.content)Request parameters supported by the Qwen3.5 Flash API on EmpirioLabs. Defaults apply when a field is omitted.
| Parameter | Type | Default | Range / values | Description |
|---|---|---|---|---|
| temperature | number | 0.7 | 0 to 2 | Sampling temperature. 0 = deterministic, 2 = maximum randomness. |
| top_p | number | 0.9 | 0 to 1 | Nucleus sampling probability mass. Lower = more focused. |
| max_tokens | number | 4096 | 1 to 32768 | Maximum tokens in the response. |
| enable_thinking | boolean | true | - | Enable extended thinking mode. Slower but improves reasoning-heavy tasks. |
| vl_high_resolution_images | boolean | true | - | Use higher resolution for input images. Better detail at higher cost. |
| max_pixels | number | 2621440 | 1 to 99999999 | Maximum pixels per input image. Larger = more detail but slower / more tokens. |
| tool_web_search | boolean | false | - | Search the web for real-time information. |
| tool_web_extractor | boolean | true | - | Extract and read content from URLs. Requires Web Search and Thinking. |
| tool_code_interpreter | boolean | true | - | Run Python code in a sandbox. Requires Thinking. |
| tool_web_search_image | boolean | true | - | Search the web for images from text descriptions. |
| tool_image_search | boolean | true | - | Find similar images from an uploaded image. |
| video_fps | number | 2 | 0.1 to 10 | Frames-per-second sampled from input video for analysis. |
| treat_images_as_video | boolean | false | - | Treat a sequence of input images as a video for temporal reasoning. |
| response_format | enum | - | - | Return the output as a valid JSON object (JSON mode). Describe the fields you want in your prompt. |
Built-in tools (billed only when invoked)
Text-to-Image Search and Image-to-Image Search use the Image Search pricing row. Each invoked image search is billed at that listed per-call rate.
When this model invokes tools (web search, code interpreter, etc.) inside a single request, the response carries a normalized usage.tool_usage map alongside the token counts. The example below shows the shape — exact field names, units, and which tools appear can vary slightly per provider:
"usage": {
"prompt_tokens": 123,
"completion_tokens": 456,
"cost_usd": 0.0042,
"tool_usage": {"web_search": 3, "code_interpreter": 1}
}The tool counts are already factored into cost_usd — they are surfaced for transparency so you can audit per-tool billing. The field is omitted when no tools were invoked.
:variant1
Supports text, image, and video input. Web search is available through tool_web_search and adds $0.01 per query when enabled. Thinking tokens are billed as output tokens. Explicit cache controls are not supported.
Variants are alternate versions of Qwen3.5 Flash with their own model id. Depending on the variant, they can differ in serving region, pricing, or supported parameters; everything else works the same way.
qwen3-5-flash:variant1On EmpirioLabs, Qwen3.5 Flash is billed pay as you go. The live rate card on this page always matches what the API charges.
Qwen3.5 Flash supports a 1M-token context window with up to 32,768 output tokens per response.
Yes. Qwen3.5 Flash serves the OpenAI-compatible Chat Completions API, so existing OpenAI SDKs work by pointing base_url at https://api.empiriolabs.ai/v1 and setting the model id to qwen3-5-flash.
Qwen3.5 Flash is available as 2 model ids: the default qwen3-5-flash plus qwen3-5-flash:variant1 (China). Variants can differ in serving region, pricing, or supported parameters; the rate cards for each are on this page.
Yes. The EmpirioLabs playground runs Qwen3.5 Flash in the browser with the same parameters the API exposes, so you can test prompts before writing code.
Create an EmpirioLabs account, then generate a key under API Keys in the dashboard. Billing is pay-as-you-go credits, so you only pay for the requests you make.
Check out our pricing or reach out if you want your own model deployed on our stack.
