DeepSeek 模型与 API

浏览 TokenHub 当前可用的 DeepSeek 模型，比较价格、上下文窗口和支持能力，并通过一套兼容 OpenAI 的 API 工作流完成接入。

查看 DeepSeek 模型获取 API Key

DeepSeek 模型与 API 定价

比较当前 DeepSeek API 价格、输入与输出 token 成本、上下文窗口和支持端点。打开模型页可查看完整规格与请求示例。

API 价格模型参数

单独比较各模型的输入、输出与缓存读取价格，避免与能力参数混在一起。

模型名称输入/ 百万 Token输出/ 百万 Token缓存读取/ 百万 Token

DeepSeek

DeepSeek R1deepseek-r1

$0.5714$2.2857$0.2286

DeepSeek

DeepSeek V3deepseek-v3

$0.2857$1.1429$0.1143

DeepSeek

DeepSeek V3.1 Terminusdeepseek-v3.1-terminus

$0.5714$1.7143$0.0857

DeepSeek

DeepSeek V3.2 Thinkdeepseek-v3.2-think

$0.2857$0.4286$0.0286

DeepSeek

DeepSeek V4 Flashdeepseek-v4-flash

$0.4286$1.2857$0.0143

DeepSeek

DeepSeek V4 Flash Vision Expdeepseek-v4-flash-vision-exp

$0.4286$1.2857$0.0143

DeepSeek

DeepSeek V4 Prodeepseek-v4-pro

$1.2857$3.8571$0.0429

比较上下文窗口、最大输出、推理、工具调用、端点和发布日期。

模型名称模态上下文窗口最大输出推理工具调用端点发布日期

DeepSeek

DeepSeek R1deepseek-r1

128K

32.8K

✓

OpenAI / Anthropic

2025年1月20日

DeepSeek

DeepSeek V3deepseek-v3

128K

16K

—

OpenAI / Anthropic

2024年12月26日

DeepSeek

DeepSeek V3.1 Terminusdeepseek-v3.1-terminus

128K

64K

—

OpenAI / Anthropic

2025年9月22日

DeepSeek

DeepSeek V3.2 Thinkdeepseek-v3.2-think

128K

64K

—

OpenAI / Anthropic

2025年12月1日

DeepSeek

DeepSeek V4 Flashdeepseek-v4-flash

384K

✓

OpenAI / Responses

2026年4月24日

DeepSeek

DeepSeek V4 Flash Vision Expdeepseek-v4-flash-vision-exp

384K

✓

OpenAI / Responses / Anthropic

2026年8月21日

DeepSeek

DeepSeek V4 Prodeepseek-v4-pro

384K

✓

OpenAI / Responses

2026年4月24日

目录数据说明

价格、模型可用性、上下文窗口和端点支持来自 TokenHub 当前模型目录。规格与可用性可能调整，生产环境上线前请在模型详情页再次确认。

最后更新: 2026-08-25

开始调用 DeepSeek API

通过 DeepSeek OpenAI API 兼容方式调用 Chat Completions 或 Responses，也可以使用 DeepSeek Claude Messages API。页面提供 OpenAI SDK 调用 DeepSeek 的 Python 和 Node.js 示例；是否支持流式输出取决于所选端点。

01创建 TokenHub API Key
02选择当前可用的 DeepSeek 模型
03选择 API 协议
04使用发布的端点和模型 ID
05发送第一个请求

获取 API Key 阅读 API 文档

选择 API 协议

OpenAI ChatPOST /v1/chat/completionsOpenAI ResponsesPOST /v1/responsesClaude MessagesPOST /v1/messages

OpenAI SDK · TypeScriptOpenAI SDK · PythoncURLTypeScript fetchPython requests

import OpenAI from "openai"

const client = new OpenAI({
  apiKey: process.env.TOKENHUB_API_KEY,
  baseURL: "https://us-api.tokenhub.com/v1",
})

const result = await client.chat.completions.create({
  "model": "deepseek-v3.2-think",
  "messages": [
    {
      "role": "user",
      "content": "Explain why low latency matters for an AI product in one sentence."
    }
  ]
})
console.log(result.choices[0]?.message?.content)

import json
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("TOKENHUB_API_KEY"),
    base_url="https://us-api.tokenhub.com/v1",
)

request = json.loads("{\"model\":\"deepseek-v3.2-think\",\"messages\":[{\"role\":\"user\",\"content\":\"Explain why low latency matters for an AI product in one sentence.\"}]}")
result = client.chat.completions.create(**request)
print(result.choices[0].message.content)

curl 'https://us-api.tokenhub.com/v1/chat/completions' \
  -X 'POST' \
  -H "Authorization: Bearer $TOKENHUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "deepseek-v3.2-think",
  "messages": [
    {
      "role": "user",
      "content": "Explain why low latency matters for an AI product in one sentence."
    }
  ]
}'

const response = await fetch("https://us-api.tokenhub.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.TOKENHUB_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "deepseek-v3.2-think",
    "messages": [
      {
        "role": "user",
        "content": "Explain why low latency matters for an AI product in one sentence."
      }
    ]
  }),
})
const data = await response.json()
console.log(data)

import os
import requests

response = requests.request(method="POST", url="https://us-api.tokenhub.com/v1/chat/completions",
    headers={
        "Authorization": f"Bearer {os.environ['TOKENHUB_API_KEY']}",
        "Content-Type": "application/json",
    },
    json=__import__("json").loads("{\"model\":\"deepseek-v3.2-think\",\"messages\":[{\"role\":\"user\",\"content\":\"Explain why low latency matters for an AI product in one sentence.\"}]}"),
)
response.raise_for_status()
print(response.json())

OpenAI SDK · TypeScriptOpenAI SDK · PythoncURLTypeScript fetchPython requests

import OpenAI from "openai"

const client = new OpenAI({
  apiKey: process.env.TOKENHUB_API_KEY,
  baseURL: "https://us-api.tokenhub.com/v1",
})

const result = await client.responses.create({
  "model": "deepseek-v3.2-think",
  "input": "Explain why low latency matters for an AI product in one sentence."
})
console.log(result.output_text)

import json
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("TOKENHUB_API_KEY"),
    base_url="https://us-api.tokenhub.com/v1",
)

request = json.loads("{\"model\":\"deepseek-v3.2-think\",\"input\":\"Explain why low latency matters for an AI product in one sentence.\"}")
result = client.responses.create(**request)
print(result.output_text)

curl 'https://us-api.tokenhub.com/v1/responses' \
  -X 'POST' \
  -H "Authorization: Bearer $TOKENHUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "deepseek-v3.2-think",
  "input": "Explain why low latency matters for an AI product in one sentence."
}'

const response = await fetch("https://us-api.tokenhub.com/v1/responses", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.TOKENHUB_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "deepseek-v3.2-think",
    "input": "Explain why low latency matters for an AI product in one sentence."
  }),
})
const data = await response.json()
console.log(data)

import os
import requests

response = requests.request(method="POST", url="https://us-api.tokenhub.com/v1/responses",
    headers={
        "Authorization": f"Bearer {os.environ['TOKENHUB_API_KEY']}",
        "Content-Type": "application/json",
    },
    json=__import__("json").loads("{\"model\":\"deepseek-v3.2-think\",\"input\":\"Explain why low latency matters for an AI product in one sentence.\"}"),
)
response.raise_for_status()
print(response.json())

cURLTypeScript fetchPython requests

curl 'https://us-api.tokenhub.com/v1/messages' \
  -X 'POST' \
  -H "Authorization: Bearer $TOKENHUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "deepseek-v3.2-think",
  "max_tokens": 1024,
  "messages": [
    {
      "role": "user",
      "content": "Explain why low latency matters for an AI product in one sentence."
    }
  ]
}'

const response = await fetch("https://us-api.tokenhub.com/v1/messages", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.TOKENHUB_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "deepseek-v3.2-think",
    "max_tokens": 1024,
    "messages": [
      {
        "role": "user",
        "content": "Explain why low latency matters for an AI product in one sentence."
      }
    ]
  }),
})
const data = await response.json()
console.log(data)

import os
import requests

response = requests.request(method="POST", url="https://us-api.tokenhub.com/v1/messages",
    headers={
        "Authorization": f"Bearer {os.environ['TOKENHUB_API_KEY']}",
        "Content-Type": "application/json",
    },
    json=__import__("json").loads("{\"model\":\"deepseek-v3.2-think\",\"max_tokens\":1024,\"messages\":[{\"role\":\"user\",\"content\":\"Explain why low latency matters for an AI product in one sentence.\"}]}"),
)
response.raise_for_status()
print(response.json())

应该选择哪个 DeepSeek 模型？

按 DeepSeek API 的实际任务选择模型；接入前再确认 DeepSeek API 价格、上下文窗口与端点支持情况。

API 任务	优先查看	适合场景	上线前确认
高频、注重成本的 API 调用	DeepSeek V4 Flash	聊天、摘要、内容生成和批处理等重视快速迭代的任务。	DeepSeek API 价格、吞吐量与输出 token 成本
复杂推理	DeepSeek R1	多步骤分析、代码推理等更看重答案质量而非延迟的任务。	推理延迟、输出长度与单次请求总成本
通用生产任务	DeepSeek V3.2 Think	助手、信息提取等通过一个 DeepSeek API 接入覆盖的日常产品功能。	任务准确率、端点支持与生产环境价格
长输入和长对话	DeepSeek V4 Flash	提示词、文档或对话历史成为限制的长上下文 DeepSeek API 请求。	上下文窗口、输入 token 价格与流式输出支持
高质量或高风险交付	DeepSeek V4 Pro	最终交付更看重能力上限，而不是追求最低单位成本的任务。	具体任务质量、延迟，以及与 Flash 的成本差异