
Trillion-scale MoE flagship for coding, long-horizon agents, and professional work, with image and video understanding across a 1M-token context.
Trillion-scale MoE flagship for coding, long-horizon agents, and professional work, with image and video understanding across a 1M-token context.
Supports text, image, and video input, thinking mode with enable_thinking and thinking_budget up to 262144 tokens, function calling, structured output including strict JSON Schema, and five built-in tools: tool_web_search, tool_web_extractor, tool_code_interpreter, tool_web_search_image, and tool_image_search. Thinking tokens are billed as output tokens.
Also known as Alibaba Cloud Qwen3.8 Max
qwen3-8-max/v1/chat/completionsPOST/v1/responsesPOST/v1/messagesPOST/v1beta/models/qwen3-8-max:generateContentqwen3.8-maxLive pay-as-you-go rates from the EmpirioLabs catalog. You are billed only for what you use, with no monthly minimum.
Qwen3.8 Max 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-max. 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-max",
"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-max",
messages=[{"role": "user", "content": "Write a haiku about the ocean."}],
)
print(response.choices[0].message.content)Request parameters supported by the Qwen3.8 Max 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 | true | - | Search the web for real-time information. Adds $0.02 to the request cost for each invoked call. |
| 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. |
Text, image, and video input are supported. Web search, web extractor, code interpreter, text-to-image search, and image-to-image search are optional built-in tools exposed through tool_* parameters. Web search, text-to-image search, and image-to-image search add $0.02 for each invoked call; web extractor and code interpreter run at no extra cost. Web extractor requires web search, and both web extractor and code interpreter require thinking. A single request can invoke a tool more than once, and each invoked call is billed. Thinking tokens are billed as output 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, "code_interpreter": 1}
}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.
:variant1
Text, image, and video input are supported. Web search, web extractor, code interpreter, text-to-image search, and image-to-image search are optional built-in tools exposed through tool_* parameters. Web search, text-to-image search, and image-to-image search add $0.02 for each invoked call; web extractor and code interpreter run at no extra cost. Web extractor requires web search, and both web extractor and code interpreter require thinking. A single request can invoke a tool more than once, and each invoked call is billed. Thinking tokens are billed as output tokens.
Variants are alternate versions of Qwen3.8 Max 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.
qwen3-8-max:variant1qwen3.8-max:variant1On EmpirioLabs, Qwen3.8 Max is billed pay as you go: Input $2.00 per 1M prompt tokens; Output $6.00 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 Max supports a 1M-token context window with up to 131,072 output tokens per response.
Yes. Qwen3.8 Max 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-max.
Qwen3.8 Max is available as 2 model ids: the default qwen3-8-max plus qwen3-8-max: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 Qwen3.8 Max 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.