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A powerful language model developed by MiniMax AI, designed to excel in tasks requiring extensive context processing and reasoning capabilities. With a total of 456 billion parameters, of which 45.9 billion are activated per token, this model utilizes a hybrid architecture that combines various attention mechanisms to optimize performance across a wide array of applications.
Only model
and messages
are required parameters for this model (and we’ve already filled them in for you in the example), but you can include optional parameters if needed to adjust the model’s behavior. Below, you can find the corresponding , which lists all available parameters along with notes on how to use them.
If you need a more detailed walkthrough for setting up your development environment and making a request step by step — feel free to use our .
Creates a chat completion using a language model, allowing interactive conversation by predicting the next response based on the given chat history. This is useful for AI-driven dialogue systems and virtual assistants.
The maximum number of tokens that can be generated in the chat completion. This value can be used to control costs for text generated via API.
256
If set to True, the model response data will be streamed to the client as it is generated using server-sent events.
false
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both.
0.1
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.
0.95
Mask (replace with ***) content in the output that involves private information, including but not limited to email, domain, link, ID number, home address, etc. Defaults to False, i.e. enable masking.
false
Controls which (if any) tool is called by the model. none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools. Specifying a particular tool via {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool. none is the default when no tools are present. auto is the default if tools are present.
none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools.
An object specifying the format that the model must output.
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