Ali

Qwen3-Max-2026-01-23

ali/qwen3-max-2026-01-23
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

通义千问3系列Max模型,相较2025年9月23日快照,此版本实现思考模式和非思考模式的有效融合,模型整体效果得到全方位的大幅度提升。在思考模式下,同时发布Web搜索、Web信息提取和代码解释器工具能力,使得模型在慢思考的同时,能够通过引入外部工具,以更高的准确性解决更有难度的问题。此版本为2026年1月23日快照。

Input / output modalities
文本 to 文本
Reference input / output price
Input¥2.5Output¥10per 1M tokens
Context window
256K
Added to catalog
Jan 27, 2026

Providers and pricing

ProviderInput lengthInput /MOutput /MCached /MContextMax outputDetails
Ali≤ 32K¥2.5¥10¥0256K32K
32K – 128K¥4¥16¥0
≥ 128K¥7¥18¥0

Ali

Latency
0.79s
Throughput
65 tokens/s
Context
256K

Pricing

Input
¥2.5/M tokens
Output
¥10/M tokens
Cached
¥0/M tokens

Tiered pricing

Pricing varies by input token range.

0–32K Token

Input tier
¥2.5/M tokens
Output tier
¥10/M tokens
Cached tier
¥0/M tokens

32K–128K Token

Input tier
¥4/M tokens
Output tier
¥16/M tokens
Cached tier
¥0/M tokens

128K–∞ Token

Input tier
¥7/M tokens
Output tier
¥18/M tokens
Cached tier
¥0/M tokens

Additional pricing

Tools · Web search preview
¥0.006

Specifications

Context
256K
Max output
32K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Qwen3-Max-2026-01-23 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-max-2026-01-23", 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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