Ali

Qwen3.6-Max-Preview

ali/qwen3.6-max-preview
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Qwen3.6系列中规模最大、综合能力最强的Max模型Preview版本,当前开放纯文本模型能力供体验。相较于此前发布的Qwen3-Max和Qwen3.6-Plus,本模型在vibe coding能力上进一步提升、coding agent执行更加高效、前端编程开发能力显著提升;长尾知识能力进一步升级。

Input / output modalities
文本 to 文本
Reference input / output price
Input¥9Output¥54per 1M tokens
Context window
256K
Added to catalog
Apr 21, 2026

Providers and pricing

ProviderInput lengthInput /MOutput /MCached /MContextMax outputDetails
Ali≤ 128K¥9¥54¥0.9256K64K
128K – 256K¥15¥90¥1.5

Ali

Latency
0.82s
Throughput
72 tokens/s
Context
256K

Pricing

Input
¥9/M tokens
Output
¥54/M tokens
Cached
¥0.9/M tokens
Cache write (1 hour)
¥18.75/M tokens
Cache write (5 minutes)
¥18.75/M tokens

Tiered pricing

Pricing varies by input token range.

0–128K Token

Input tier
¥9/M tokens
Output tier
¥54/M tokens
Cached tier
¥0.9/M tokens

128K–256K Token

Input tier
¥15/M tokens
Output tier
¥90/M tokens
Cached tier
¥1.5/M tokens

Additional pricing

Tools · Web search preview
¥0.006
Cache write price 5m
¥18.75
Cache write price 1h
¥18.75

Specifications

Context
256K
Max output
64K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Qwen3.6-Max-Preview code examples and API guide

Modelmesh normalizes requests and responses across service providers behind one consistent API.

Modelmesh provides an OpenAI-compatible Completion API for more than 300 models and service providers. Call it directly, through the OpenAI SDK, or with supported third-party SDKs.

Modelmesh-specific request headers in these examples are optional. When supplied, your application can appear on the Modelmesh rankings.

Supported endpointsSelect an endpoint to switch the example below.
/v1/chat/completions
from openai import OpenAI API_KEY = "$SSY_API_KEY" client = OpenAI( base_url="https://router.shengsuanyun.com/api/v1", api_key=API_KEY, ) try: completion = client.chat.completions.create( model="ali/qwen3.6-max-preview", messages=[{"role": "user", "content": "Which number is larger, 9.11 or 9.8?"}], temperature=0.6, top_p=0.7, stream=True, ) response_text = "" for chunk in completion: if chunk.choices and chunk.choices[0].delta.content is not None: content = chunk.choices[0].delta.content print(content, end="", flush=True) response_text += content except Exception as error: print(f"Request failed: {error}")
                
              

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