Meta: Llama 3.1 405B Instruct

meta-llama/llama-3.1-405b-instruct

Created Jul 23, 202410,000 context

$3.50/M input tokens$3.50/M output tokens

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. Usage of this model is subject to Meta's Acceptable Use Policy.

Providers for Llama 3.1 405B Instruct

OpenRouter routes requests to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.

Performance for Llama 3.1 405B Instruct

Compare different providers across OpenRouter

Apps using Llama 3.1 405B Instruct

Top public apps this month

Recent activity on Llama 3.1 405B Instruct

Total usage per day on OpenRouter

Prompt

20.1M

Completion

2.52M

Prompt tokens measure input size. Reasoning tokens show internal thinking before a response. Completion tokens reflect total output length.

Uptime stats for Llama 3.1 405B Instruct

Uptime stats for Llama 3.1 405B Instruct across all providers

Sample code and API for Llama 3.1 405B Instruct

OpenRouter normalizes requests and responses across providers for you.

OpenRouter provides an OpenAI-compatible completion API to 400+ models & providers that you can call directly, or using the OpenAI SDK. Additionally, some third-party SDKs are available.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

See the Request docs for all possible fields, and Parameters for explanations of specific sampling parameters.