DeepSeek V3 | 685B MoE LLM API Pricing

Name: DeepSeek Chat API
Brand: deepseek
Price: 0.32 USD
Availability: InStock

deepseek/deepseek-chat

Tanggal rilis: 2024-12-27

163,840 context · $0.32/M input tokens · $0.89/M output tokens

DeepSeek-V3 is the latest model from the DeepSeek team, building upon the instruction following and coding abilities of the previous versions. Pre-trained on nearly 15 trillion tokens, the reported evaluations...

Harga

Bayar sesuai pemakaian

Tanpa biaya di muka, bayar hanya sesuai penggunaan

Input$0.32 / M Tokens

Output$0.89 / M Tokens

Coba model

deepseek/deepseek-chat

Online

Hai! Saya asisten AI yang siap membantu. Ada yang bisa saya bantu?

Siap memakai model ini di coding agent lokal?Setup agent

Penggunaan API

Gunakan contoh kode berikut untuk integrasi dengan API kami:

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: 2,
});

try {
  const response = await client.chat.completions.create({
    model: 'deepseek/deepseek-chat',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  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: 2,
});

try {
  const response = await client.chat.completions.create({
    model: 'deepseek/deepseek-chat',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

Pengenalan Model

Deepseek deepseek-chat

deepseek deepseek-chat

Why It Looks Great

Large Language Model architecture for efficient processing
163840 context window for long document handling
Competitive pricing at $0.3/$1.3 per million tokens

Key Features

Context Window: 163840 tokens
Max Output: 163840 tokens
Vision: Supported
Function Calling: Supported

Specifications

Specification	Value
Provider	Deepseek
Model Type	Large Language Model (LLM)
Architecture	N/A
Context Window	163840 tokens
Max Output	163840 tokens
Input	Text
Output	Text
Vision	Supported
Function Calling	Supported

Pricing

Token Type	Cost per Million Tokens
Input	$0.3
Output	$1.3

How to Use

Write your prompt — describe the task, provide context, and specify 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-chat

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-chat",
    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-chat",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: deepseek/deepseek-chat
Provider: Deepseek

Info

Penyediadeepseek

Tipellm

Fitur yang Didukung

Input

Teks

Output

Teks

Konteks163,840

Output Maks163,840

Vision-

Function Calling✓ Didukung

Panduan Akses API

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

API Endpointchat/completions

Model IDdeepseek/deepseek-chat

Pertanyaan Umum tentang DeepSeek Chat

Berapa biaya DeepSeek Chat melalui API?+

Harga di WaveSpeedAI: $0.32 per juta token input dan $0.89 per juta token output. Prompt caching dan batch processing ditagih terpisah dan mengurangi biaya efektif pada beban kerja yang panjang dan berulang.

Berapa context window DeepSeek Chat?+

DeepSeek Chat mendukung hingga 164K token konteks dengan hingga 164K token output per permintaan.

Apakah DeepSeek Chat kompatibel dengan OpenAI?+

WaveSpeedAI menyediakan DeepSeek Chat di https://llm.wavespeed.ai/v1 melalui antarmuka Chat Completions yang kompatibel dengan OpenAI. Sebagian besar klien OpenAI SDK cukup mengganti base URL dan API key; field opsional bergantung pada model.

Bagaimana memulai dengan DeepSeek Chat?+

Masuk ke WaveSpeedAI, buat API key di Access Keys, lalu kirim permintaan ke https://llm.wavespeed.ai/v1/chat/completions dengan model id yang ditampilkan di atas. Lihat katalog model terbaru untuk ketersediaan, kemampuan, dan harga.