DeepSeek V4.1 Flash 1017 | DeepSeek Multimodal LLM API Pricing

Name: DeepSeek V4.1 Flash 1017 API
Brand: deepseek
Price: 0.3 USD
Availability: InStock

deepseek/deepseek-v4.1-flash-1017

发布时间: 2026-10-17

1,048,576 context · $0.30/M input tokens · $1.20/M output tokens

DeepSeek V4.1 Flash 1017 is the October 17, 2026 snapshot of DeepSeek V4.1 Flash, served by DeepSeek under the deepseek-flash API model name. V4.1 Flash is a sparse mixture-of-experts model...

定价

按量付费

无需预付费用，仅按实际使用量付费

输入$0.30 / M Tokens

输出$1.20 / M Tokens

Cache Read$0.0060 / M Tokens

试用模型

deepseek/deepseek-v4.1-flash-1017

在线

你好！我是乐于助人的 AI 助手。需要我帮你做什么？

准备在本地编码 Agent 中使用这个模型吗？Agent 配置

API 使用

使用以下代码示例接入我们的 API：

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 0,
});

try {
  const response = await client.chat.completions.create({
    model: 'deepseek/deepseek-v4.1-flash-1017',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  const body = response as typeof response & { error?: { message?: string } };
  if (body.error) throw new Error(body.error.message || 'LLM generation failed');
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 0,
});

try {
  const response = await client.chat.completions.create({
    model: 'deepseek/deepseek-v4.1-flash-1017',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  const body = response as typeof response & { error?: { message?: string } };
  if (body.error) throw new Error(body.error.message || 'LLM generation failed');
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

模型介绍

DeepSeek: DeepSeek V4.1 Flash 1017

DeepSeek V4.1 Flash 1017 is the October 17, 2026 snapshot of DeepSeek V4.1 Flash, served by DeepSeek under the deepseek-flash API model name. V4.1 Flash is a sparse mixture-of-experts model...

This model is available through the WaveSpeed AI OpenAI-compatible API for chat completions and compatible application workflows.

Why It Looks Great

text+image->text architecture for Text, Image to Text workloads
1048576 context window for long prompts, document analysis, and multi-turn workflows
Vision input support for image understanding and multimodal tasks
Function calling and tool-use support for agentic application workflows
Structured output support for JSON responses and schema-constrained generation
Reasoning controls available through supported parameters

Key Features

Context Window: 1048576 tokens
Max Input: 655360 tokens
Max Output: 393216 tokens
Vision: Supported
Function Calling: Supported
Structured Outputs: Supported
Image Generation: Not listed
Audio Input: Not listed
Supported Parameters: frequency_penalty, include_reasoning, logit_bias, logprobs, max_completion_tokens, max_tokens, min_p, parallel_tool_calls, presence_penalty, reasoning, reasoning_effort, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p

Specifications

Specification	Value
Provider	deepseek
Model Type	Chat Completions model
Architecture	text+image->text
Context Window	1048576 tokens
Max Input	655360 tokens
Max Output	393216 tokens
Input	Text, Image
Output	Text
Vision	Supported
Function Calling	Supported
Structured Outputs	Supported
Release Date	October 17, 2026

How to Use

Write your prompt - describe the task, provide context, and specify the desired output format.
Submit - the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: deepseek/deepseek-v4.1-flash-1017

API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="deepseek/deepseek-v4.1-flash-1017",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "deepseek/deepseek-v4.1-flash-1017",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: deepseek/deepseek-v4.1-flash-1017
Provider: deepseek

信息

提供商deepseek

类型llm

支持功能

输入

文本图像

输出

文本

上下文1,048,576

最大输出393,216

视觉✓ 支持

函数调用✓ 支持

API 访问指南

Base URLhttps://llm.wavespeed.ai/v1

API 端点chat/completions

Model IDdeepseek/deepseek-v4.1-flash-1017

关于 DeepSeek V4.1 Flash 1017 的常见问题

DeepSeek V4.1 Flash 1017 API 多少钱?+

WaveSpeedAI 定价:输入每百万 token $0.30,输出每百万 token $1.20。Prompt 缓存和批处理单独计费,可显著降低长上下文、高重复任务的实际成本。

DeepSeek V4.1 Flash 1017 的上下文窗口是多大?+

DeepSeek V4.1 Flash 1017 单次请求最多支持 1049K 上下文 token,输出最多 393K token。

DeepSeek V4.1 Flash 1017 是否兼容 OpenAI?+

WaveSpeedAI 通过 https://llm.wavespeed.ai/v1 的 OpenAI 兼容 Chat Completions 接口提供 DeepSeek V4.1 Flash 1017。大多数 OpenAI SDK 客户端只需更换 base URL 和 API Key；可选字段取决于具体模型。

如何开始使用 DeepSeek V4.1 Flash 1017?+

登录 WaveSpeedAI，在 Access Keys 中创建 API Key，然后使用上方显示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 发送请求。模型可用性、能力和价格请以当前模型目录为准。

定价