Qwen3.7 Flash is available on EmpirioLabs. It is the fast tier of Alibaba's Qwen3.7 vision-language series, built for multimodal understanding, agentic tool use, and long-context work, with a 1M token context window, switchable thinking, and text, image, and video input. It runs on an OpenAI-compatible API, so you can switch to it by changing one field.
What Qwen3.7 Flash is good at
Flash is the speed and cost tier of the Qwen3.7 family, so it suits high-volume work where you still want real reasoning available: document and screenshot understanding, video question answering, extraction pipelines, and agent loops that call tools. It reads images and video, calls tools with standard function calling, returns JSON on demand, and can search the web, run code, and read URLs through built-in tools. Both a Singapore and a China deployment are available, so you can pick the one that fits your latency and pricing needs.
How to call it
Send a standard chat completion:
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": "Summarize this quarter'"'"'s report in five bullets."}
]
}'The final answer comes back in content, and when thinking is on the model's reasoning is in reasoning_content.
Control the thinking
Thinking is on by default. Turn it off for short, latency-sensitive calls, or set a budget for how many tokens the model may spend reasoning. You can also use reasoning_effort with none, low, medium, high, or max, which maps to a budget sized for this model:
{
"model": "qwen3-7-flash",
"messages": [{"role": "user", "content": "Plan a migration and justify the order."}],
"enable_thinking": true,
"thinking_budget": 32768
}Reasoning tokens are billed as output tokens.
Images and video
Pass images and video as content parts on a user message alongside your text, then ask a question about what they show. You can attach more than one input in a single request:
{
"model": "qwen3-7-flash",
"messages": [{"role": "user", "content": [
{"type": "text", "text": "What changed between these two screenshots?"},
{"type": "image_url", "image_url": {"url": "https://example.com/before.png"}},
{"type": "image_url", "image_url": {"url": "https://example.com/after.png"}}
]}]
}Built-in tools
Qwen3.7 Flash ships with web search, a web extractor for reading URLs, a code interpreter, and text-to-image and image-to-image search. Each is a toggle, and they are billed only when the model actually invokes them. Web Extractor and Code Interpreter need thinking enabled:
{
"model": "qwen3-7-flash",
"messages": [{"role": "user", "content": "What shipped in the latest release?"}],
"tool_web_search": true
}When tools run, the response carries a usage.tool_usage map next to the token counts so you can audit exactly what was invoked.
Structured output and function calling
Use response_format with {"type": "json_object"} to force a valid JSON object, and pass tools for standard function calling when you want the model to call into your own code.
Prompt caching
Repeated prompt prefixes are cached automatically, and cached input tokens bill at a much lower rate than fresh input. If you send a long shared system prompt or document header across many requests, you get that discount without changing anything in your code.
Regions
The default qwen3-7-flash is the Singapore deployment. qwen3-7-flash:variant1 is the China deployment of the same model at lower rates. Both take the same parameters, so you can switch between them with the model field alone.
Pricing
Qwen3.7 Flash is pay as you go, billed per token. Input and output rates step down for shorter prompts and up for very long ones, cached input bills at a reduced rate, and the built-in tools cost a small per-call fee only when they run. See the live rates on the Qwen3.7 Flash model page and the pricing page, and try it in the playground.
