Llama 3.1 405B Instruct

Meta chattool_use

API ID: meta-llama/llama-3.1-405b-instruct

Input Price
$3.50
/1M tokens
Output Price
$3.50
/1M tokens

About Llama 3.1 405B Instruct

The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the frontier of open-source LLMs. Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 405B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong performance compared to leading closed-source models including GPT-4o and Claude 3.5 Sonnet in evaluations. To read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).

๐Ÿ’ฐ
Price Ranking
#1086 lowest price among 1240 Chat models

Model Specifications

Context Length
131k
Max Output
โ€”
Release Date
2024-07-23
Capabilities
chat tool_use
Input Modalities
text
Output Modalities
text

Best For

  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)

๐Ÿ’ฐ Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$2.63
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$84.00
/month
1000 tickets/day, ~800 tokens each

Meta Model Lineup

Compare all models from Meta to find the best fit

Model Input Output Context Capabilities
Llama 3.1 405B Instruct Current Free Free 131k chat tool_use
Llama 3 70B (Base) Free Free 8k chat
Llama 3 70B (Base) Free Free 8k chat
LlamaGuard 2 8B Free Free 8k chat
Llama 3 8B (Base) Free Free 8k chat
Llama 3 8B (Base) Free Free 8k chat

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๐Ÿš€ Quick Start

Get started with Llama 3.1 405B Instruct API

OpenAI-compatible SDK
from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="meta-llama/llama-3.1-405b-instruct",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)