Llama 3.3 70B Instruct | Meta Open-Source LLM API

Name: Llama 3.3 70b Instruct API
Brand: meta-llama
Price: 0.1 USD
Availability: InStock

meta-llama/llama-3.3-70b-instruct

Tanggal rilis: 2024-12-07

131,072 context · $0.10/M input tokens · $0.32/M output tokens

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...

Harga

Bayar sesuai pemakaian

Tanpa biaya di muka, bayar hanya sesuai penggunaan

Input$0.10 / M Tokens

Output$0.32 / M Tokens

Coba model

meta-llama/llama-3.3-70b-instruct

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: 'meta-llama/llama-3.3-70b-instruct',
    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: 'meta-llama/llama-3.3-70b-instruct',
    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

Meta-Llama llama-3.3-70b-instruct

meta-llama llama-3.3-70b-instruct

Why It Looks Great

Large Language Model architecture for efficient processing
131072 context window for long document handling
Competitive pricing at $0.1/$0.3 per million tokens

Key Features

Context Window: 131072 tokens
Max Output: 16384 tokens
Vision: Supported
Function Calling: Supported

Specifications

Specification	Value
Provider	Meta-Llama
Model Type	Large Language Model (LLM)
Architecture	N/A
Context Window	131072 tokens
Max Output	16384 tokens
Input	Text
Output	Text
Vision	Supported
Function Calling	Supported

Pricing

Token Type	Cost per Million Tokens
Input	$0.1
Output	$0.3

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: meta-llama/llama-3.3-70b-instruct

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="meta-llama/llama-3.3-70b-instruct",
    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": "meta-llama/llama-3.3-70b-instruct",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: meta-llama/llama-3.3-70b-instruct
Provider: Meta-Llama

Info

Penyediameta

Tipellm

Fitur yang Didukung

Input

Teks

Output

Teks

Konteks131,072

Output Maks16,384

Vision-

Function Calling✓ Didukung

Panduan Akses API

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

API Endpointchat/completions

Model IDmeta-llama/llama-3.3-70b-instruct

Pertanyaan Umum tentang Llama 3.3 70b Instruct

Berapa biaya Llama 3.3 70b Instruct melalui API?+

Harga di WaveSpeedAI: $0.10 per juta token input dan $0.32 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 Llama 3.3 70b Instruct?+

Llama 3.3 70b Instruct mendukung hingga 131K token konteks dengan hingga 16K token output per permintaan.

Apakah Llama 3.3 70b Instruct kompatibel dengan OpenAI?+

WaveSpeedAI menyediakan Llama 3.3 70b Instruct 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 Llama 3.3 70b Instruct?+

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.