Fast Qwen3.7 vision-language model for text, image, video, tool use, and agentic tasks, with implicit caching and a 1M token context.
Alibaba CloudText Generation1M contextReleased Jul 15, 2026SingaporeProprietary EndpointNewFast Qwen3.7 vision-language model for text, image, video, tool use, and agentic tasks, with implicit caching and a 1M token context.
Supports text, image, and video inputs, thinking mode with enable_thinking and thinking_budget up to 131072 tokens, function calling, structured output, web search, web extractor, code interpreter, image search tools, prefix continuation, and implicit context caching. Web Search and image-search tools are billed per invoked call. Thinking tokens are billed as output tokens.
Also known as Alibaba Cloud Qwen3.7 Flash, Qwen3.7-Flash, qwen3-7-flash
qwen3-7-flash/v1/chat/completionsPOST/v1/responsesPOST/v1/messagesPOST/v1beta/models/qwen3-7-flash:generateContentqwen3.7-flashLive pay-as-you-go rates from the EmpirioLabs catalog. You are billed only for what you use, with no monthly minimum.
Qwen3.7 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 qwen3-7-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": "qwen3-7-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="qwen3-7-flash",
messages=[{"role": "user", "content": "Write a haiku about the ocean."}],
)
print(response.choices[0].message.content)Request parameters supported by the Qwen3.7 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 65536 | 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 131072 | 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 $0.03 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. |
Token pricing is tiered by prompt size and steps up above 32K and again above 256K input tokens. Cached prompt tokens are billed at the implicit cache rate for the matching tier. Web Search, Text-to-Image Search, and Image-to-Image Search are billed only when invoked.
Text-to-Image Search and Image-to-Image Search use the Image Search pricing row. 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. Tool counts are already factored into cost_usd and are surfaced for transparency.
:variant1
China pricing is discounted versus Singapore. Token pricing is tiered by prompt size and steps up above 32K and again above 256K input tokens. Implicit cache input uses the cached-token row. Web Search, Text-to-Image Search, and Image-to-Image Search are billed only when invoked.
Text-to-Image Search and Image-to-Image Search use the Image Search pricing row. China paid tool calls are $0.01 each. Thinking tokens are billed as output tokens.
Variants are alternate versions of Qwen3.7 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.
qwen3-7-flash:variant1On EmpirioLabs, Qwen3.7 Flash is billed pay as you go. The live rate card on this page always matches what the API charges.
Qwen3.7 Flash supports a 1M-token context window with up to 65,536 output tokens per response.
Yes. Qwen3.7 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 qwen3-7-flash.
Qwen3.7 Flash is available as 2 model ids: the default qwen3-7-flash plus qwen3-7-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 Qwen3.7 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.
