Meta LLaMA 3.1 Models

Other Generally Available

Official repository to use and implement LLaMA 3.1 models, Meta's state-of-the-art large language models.

Context

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tokens

Input

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per MTok

Output

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per MTok

About

Official repository to use and implement LLaMA 3.1 models, Meta's state-of-the-art large language models.

Name	Type	Default	Description
`frequency_penalty`	number	0	Penalize tokens by their frequency so far. Positive values reduce repetition.
`max_completion_tokens`	integer	—	Maximum number of tokens the model may generate in the response.
`presence_penalty`	number	0	Penalize tokens that have appeared at all so far. Positive values encourage new topics.
`response_format`	one of	—	Constrain output to a JSON schema or an enum (structured outputs).
`seed`	integer	—	Deterministic seed for sampling. Same seed + same prompt produces identical output.
`stop`	array	—	Up to 4 sequences where the API will stop generating tokens.
`stream`	boolean	false	Stream partial responses as Server-Sent Events.
`temperature`	number	1	Sampling temperature; higher values produce more random output. 0 is deterministic.
`tool_choice`	one of	—	Controls which (if any) tool is called: "none", "auto", "required", or a specific tool.
`tools`	array	—	List of tools (functions) the model may call.
`top_p`	number	1	Nucleus sampling: consider only tokens whose cumulative probability ≥ top_p.

Standard OpenAI-compatible parameters. Consult the provider docs for model-specific behaviour.