DeepSeek

DeepSeek-V4-Flash-Vision-Exp

deepseek/deepseek-v4-flash-vision-exp
/v1/chat/completions/v1/messages/v1/responses/v1/completions/v1beta/models/*/v1/models/*

DeepSeek V4 Flash Vision Exp是DeepSeek推出的DeepSeek V4 Flash 0731实验版视觉能力版本,新增图像理解能力,同时在智能代理、推理以及世界知识等文本能力方面与基础模型保持同等水平。该模型为稀疏混合专家模型,总参数量2840亿,激活参数量130亿。适用于文档与图表理解、视觉问答,以及文本与图像交替处理的多模态智能代理工作流。

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
Aug 24, 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
0.55s
Throughput
164 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/v1/completions/v1beta/models/*/v1/models/*

DeepSeek-V4-Flash-Vision-Exp 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-flash-vision-exp", 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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