DeepSeek

DeepSeek-V4.1-Flash

deepseek/deepseek-v4.1-flash
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

DeepSeek V4.1Flash 的中间版本内测。采用了新的模型结构,原生多模态支持、能力 更强、速度更快、且成本更低。

Input / output modalities
文本 · 图像 to 文本
Reference input / output price
Input¥1Output¥4per 1M tokens
Context window
1M
Added to catalog
Sep 9, 2026

Providers and pricing

ProviderTime-based pricing (Beijing Time)Input /MOutput /MCached /MContextMax outputDetails
DeepSeek
Mon–Fri09:00-12:0014:00-18:00Input ¥2Output ¥8Cached ¥0.04
¥1¥4¥0.021M384K

DeepSeek

Latency
11.41s
Throughput
183 tokens/s
Context
1M

Pricing

Input
¥1/M tokens
Output
¥4/M tokens
Cached
¥0.02/M tokens

Time-based pricing (Beijing Time)

The prices below apply during the listed Beijing Time periods; base pricing applies at other times.

Applicable period

Mon–Fri09:00-12:0014:00-18:00

peak

Input
¥2/M tokens
Output
¥8/M tokens
Cached
¥0.04/M tokens

Specifications

Context
1M
Max output
384K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

DeepSeek-V4.1-Flash 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="deepseek/deepseek-v4.1-flash", 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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