Qwen3.6-Flash

Qwen3.6-Flash is Alibaba’s native vision language Flash model, available through Starrise AI via an OpenAI-compatible API. Compared to Qwen3.5-Flash, it delivers significant improvements in agentic coding, math/code reasoning, and spatial intelligence.

Key Capabilities

OpenAI compatible — Drop-in replacement for the OpenAI SDK with no code changes required
1M token context — Supports large-scale documents and multi-turn conversations, up to 66K output tokens
Multimodal input — Supports text, image, and video input
Agentic coding — Significant improvement on coding agent benchmarks
Reasoning mode — Enable built-in chain-of-thought via the enable_thinking parameter
Built-in tools — Supports web search, code interpreter, webpage scraping, and image search via the Responses API

Quick Example

curl https://ai.alad.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.6-flash",
    "messages": [
      { "role": "user", "content": "Explain quantum entanglement in simple terms." }
    ]
  }'

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://ai.alad.com/v1"
)

response = client.chat.completions.create(
    model="qwen3.6-flash",
    messages=[
        {"role": "user", "content": "Explain quantum entanglement in simple terms."}
    ]
)

print(response.choices[0].message.content)

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://ai.alad.com/v1"
)

stream = client.chat.completions.create(
    model="qwen3.6-flash",
    messages=[
        {"role": "user", "content": "Write a short poem about the ocean."}
    ],
    stream=True
)

for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="")

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://ai.alad.com/v1"
)

completion = client.chat.completions.create(
    model="qwen3.6-flash",
    messages=[
        {"role": "user", "content": "Solve this math problem: x² + 5x + 6 = 0, find x."}
    ],
    extra_body={"enable_thinking": True},
    stream=True
)

for chunk in completion:
    if chunk.choices and chunk.choices[0].delta:
        delta = chunk.choices[0].delta
        if hasattr(delta, "reasoning_content") and delta.reasoning_content:
            print(delta.reasoning_content, end="", flush=True)
        if delta.content:
            print(delta.content, end="", flush=True)

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://ai.alad.com/v1"
)

response = client.chat.completions.create(
    model="qwen3.6-flash",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Please describe this image."},
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://example.com/photo.jpg"
                        # Or base64: "url": "data:image/png;base64,iVBORw0KGgo..."
                    }
                }
            ]
        }
    ],
    max_completion_tokens=300
)

print(response.choices[0].message.content)

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://ai.alad.com/v1"
)

response = client.chat.completions.create(
    model="qwen3.6-flash",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Please summarize the content of this video."},
                {
                    "type": "video_url",
                    "video_url": {
                        "url": "https://example.com/sample.mp4"
                        # Or base64: "url": "data:video/mp4;base64,AAAAIGZ0eXBpc29t..."
                    }
                }
            ]
        }
    ],
    max_completion_tokens=300
)

print(response.choices[0].message.content)

curl https://ai.alad.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.6-flash",
    "messages": [
      {
        "role": "user",
        "content": [
          {"type": "text", "text": "Please describe this image."},
          {"type": "image_url", "image_url": {"url": "data:image/png;base64,iVBORw0KGgo..."}}
        ]
      }
    ],
    "max_completion_tokens": 300
  }'

Note: Both image_url and video_url support remote URLs (https://...) and base64 data URIs (data:image/png;base64,... / data:video/mp4;base64,...). Image tokens and video tokens are reflected in usage.prompt_tokens_details.

Parameters

Parameter	Type	Required	Description
`model`	string	Yes	Must be `qwen3.6-flash`
`messages`	array	Yes	Array of `{ role, content }` objects. Supports `image_url` and `video_url` multimodal input
`max_completion_tokens`	integer	No	Maximum number of tokens to generate
`temperature`	float	No	`0`–`2`, controls randomness, default `1`
`stream`	boolean	No	Enable SSE streaming, default `false`
`top_p`	float	No	Nucleus sampling threshold, default `1`
`stop`	array	No	Stop sequences. Must be array format, default `null`
`enable_thinking`	boolean	No	Enable reasoning mode via `extra_body`, default `false`

API Reference

View the interactive API Playground for Qwen3.6-Flash.

Quick Start

Models

Resources

Key Capabilities

Quick Example

Parameters

API Reference

​Key Capabilities

​Quick Example

​Parameters

API Reference

Key Capabilities

Quick Example

Parameters