Omni-modal reasoner that reads text, images, audio, and video and answers in text, with a 1M token context, thinking, and native web search.
Alibaba CloudText Generation1M contextReleased Sep 17, 2026SingaporeProprietary EndpointNewOmni-modal reasoner that reads text, images, audio, and video and answers in text, with a 1M token context, thinking, and native web search.
Supports text, image, audio, and video input, thinking mode with enable_thinking and thinking_budget up to 262144 tokens, function calling, structured output including strict JSON Schema, and the tool_web_search built-in tool. Thinking tokens are billed as output tokens.
Also known as Alibaba Cloud Qwen3.8 Omni Flash
qwen3-8-omni-flash/v1/chat/completionsPOST/v1/responsesPOST/v1/messagesPOST/v1beta/models/qwen3-8-omni-flash:generateContentqwen3.8-omni-flashLive pay-as-you-go rates from the EmpirioLabs catalog. You are billed only for what you use, with no monthly minimum.
Qwen3.8 Omni 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 qwen3-8-omni-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": "qwen3-8-omni-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="qwen3-8-omni-flash",
messages=[{"role": "user", "content": "Write a haiku about the ocean."}],
)
print(response.choices[0].message.content)Request parameters supported by the Qwen3.8 Omni 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 is deterministic and 2 is maximum randomness. |
| top_p | number | 0.9 | 0 to 1 | Nucleus sampling probability mass. Lower values make outputs more focused. |
| max_tokens | number | 4096 | 1 to 131072 | Maximum output tokens. |
| stop | string | - | - | Up to 4 strings where the model will stop generating further tokens. |
| enable_thinking | boolean | true | - | Enable reasoning before answering. |
| reasoning_effort | enum | medium | none, low, medium, high, max | Reasoning effort level. none disables thinking. low, medium, high, and max set bounded thinking budgets sized to the selected model. |
| thinking_budget | number | 32768 | 1 to 262144 | Maximum tokens reserved for reasoning when thinking is enabled. |
| vl_high_resolution_images | boolean | true | - | Use higher resolution processing for image inputs. |
| max_pixels | number | 2621440 | 4096 to 16777216 | Maximum pixel count per image when high resolution processing is disabled. |
| video_fps | number | 2 | 0.1 to 10 | Frames per second to sample from video inputs. |
| treat_images_as_video | boolean | false | - | Treat a sequence of images as video frames. |
| tool_web_search | boolean | false | - | Search the web for real-time information. Adds $0.02 to the request cost for each invoked call. |
| disable_formatting | boolean | false | - | Return raw provider-style output without EmpirioLabs source formatting where supported. |
| response_format | enum | - | - | Constrain the output to valid JSON. Use JSON mode for any JSON object, or supply a JSON Schema to force an exact response shape. |
Text, image, audio, and video input are supported, and the model replies in text. Thinking is on by default; use enable_thinking to turn it off and thinking_budget to cap it at up to 262144 tokens. Thinking tokens are billed as output tokens. Web search is an optional built-in tool exposed through tool_web_search and adds $0.02 for each invoked call; a single request can invoke it more than once, and each invoked call is billed. For audio input, pass the file as a URL or a base64 data URI. A video's soundtrack is billed as audio tokens alongside its video tokens.
When this model invokes built-in tools inside a single request, the response carries a normalized usage.tool_usage map alongside the token counts:
"usage": {
"prompt_tokens": 123,
"completion_tokens": 456,
"cost_usd": 0.0042,
"tool_usage": {"web_search": 3}
}Tool counts are already factored into cost_usd and are surfaced for transparency so you can audit per-tool billing. The field is omitted when no tools were invoked.
On EmpirioLabs, Qwen3.8 Omni Flash is billed pay as you go: Input $0.30 per 1M prompt tokens; Output $0.94 per 1M generated tokens; Web search $0.02 per call when invoked. The live rate card on this page always matches what the API charges.
Qwen3.8 Omni Flash supports a 1M-token context window with up to 131,072 output tokens per response.
Yes. Qwen3.8 Omni 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 qwen3-8-omni-flash.
Yes. The EmpirioLabs playground runs Qwen3.8 Omni 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.
