Ali

Qwen3.5-9B

ali/qwen3.5-9b
/v1/chat/completions/v1/messages/v1/responses

Qwen3.5-9B 是通义千问团队推出的原生多模态大语言模型,拥有 9B 参数。作为 Qwen3.5 系列的轻量级 Dense 模型,它采用门控 Delta 网络与门控注意力相结合的高效混合架构,原生支持 256K 上下文长度,并可扩展至约 100 万 tokens。模型通过早期融合训练实现了统一的视觉语言基础能力,支持文本、图像和视频理解。模型默认启用思考模式(Thinking Mode),支持工具调用,并覆盖 201 种语言和方言

Input / output modalities
文本 · 图像 · 视频 to 文本
Reference input / output price
Input¥0.5Output¥1.5per 1M tokens
Context window
256K
Added to catalog
Aug 5, 2026

Providers and pricing

ProviderInput /MOutput /MCached /MContextMax outputDetails
siliconflow¥0.5¥1.5¥0256K64K

siliconflow

Latency
1.56s
Throughput
38 tokens/s
Context
256K

Pricing

Input
¥0.5/M tokens
Output
¥1.5/M tokens
Cached
¥0/M tokens

Specifications

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

Qwen3.5-9B 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/qwen3.5-9b", 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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