Llama 3 8b Instruct | Meta LLM API

Name: Llama 3 8b Instruct API
Brand: meta-llama
Price: 0.03 USD
Availability: InStock

Uso da API

Use os exemplos de código abaixo para integrar com nossa API:

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-3-8b-instruct",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

Introdução do modelo

Meta-Llama llama-3-8b-instruct

Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors

Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This 8B instruct-tuned version was optimized for high quality dialogue usecases.

It has demonstrated strong performance compared to leading closed-source models in human evaluations.

To read more about the model release, click here. Usage of this model is subject to Meta's Acceptable Use Policy.

Why It Looks Great

Large Language Model architecture for efficient processing
8192 context window for long document handling
Competitive pricing at $0.0/$0.0 per million tokens

Key Features

Context Window: 8192 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	8192 tokens
Max Output	16384 tokens
Input	Text
Output	Text
Vision	Supported
Function Calling	Supported

Pricing

Token Type	Cost per Million Tokens
Input	$0.0
Output	$0.0

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-3-8b-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-3-8b-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-3-8b-instruct",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: meta-llama/llama-3-8b-instruct
Provider: Meta-Llama

Perguntas frequentes sobre Llama 3 8b Instruct

Quanto custa Llama 3 8b Instruct via API?+

Preços no WaveSpeedAI: $0.03 por milhão de tokens de entrada e $0.04 por milhão de tokens de saída. Prompt caching e batch processing são cobrados separadamente e reduzem o custo efetivo em cargas longas e repetitivas.

Qual é a janela de contexto do Llama 3 8b Instruct?+

Llama 3 8b Instruct suporta até 8K tokens de contexto e até 16K tokens de saída por requisição.

Llama 3 8b Instruct é compatível com OpenAI?+

Sim. O WaveSpeedAI expõe o Llama 3 8b Instruct através de um endpoint compatível com OpenAI em https://llm.wavespeed.ai/v1. Aponte o SDK oficial da OpenAI para esta base URL com sua chave API do WaveSpeedAI — sem outras alterações no código.

Como começo a usar o Llama 3 8b Instruct?+

Entre no WaveSpeedAI, crie uma chave API em Access Keys, então envie uma requisição para https://llm.wavespeed.ai/v1/chat/completions com o model id mostrado acima. Contas novas recebem créditos grátis para avaliar o Llama 3 8b Instruct.

Preços