Z.ai: GLM 4.7 Flash – API Quickstart

Sample code and API for GLM 4.7 Flash

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Make your first request

Use z-ai/glm-4.7-flash with the OpenRouter API:

OpenRouter supports reasoning-enabled models that can show their step-by-step thinking process. Use the reasoning parameter in your request to enable reasoning, and access the reasoning_details array in the response to see the model's internal reasoning before the final answer. When continuing a conversation, preserve the complete reasoning_details when passing messages back to the model so it can continue reasoning from where it left off. Learn more about reasoning tokens.

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Using third-party SDKs

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Endpoint

POSThttps://openrouter.ai/api/v1/chat/completions

AuthorizationBearer $OPENROUTER_API_KEY

Content-Typeapplication/json

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X-Titleoptional — your site name, for rankings

Modelz-ai/glm-4.7-flash

Parameters

Name	Type	Default	Description
`reasoning`	map	—	Controls reasoning behavior for models that support thinking tokens, including whether reasoning is enabled, the reasoning effort, maximum reasoning tokens, and whether reasoning is excluded from the response.
`max_tokens`	integer	—	This sets the upper limit for the number of tokens the model can generate in response.
`temperature`	float	`1`	This setting influences the variety in the model's responses.
`top_p`	float	`1`	This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P.
`stop`	array	—	Stop generation immediately if the model encounter any token specified in the stop array.
`frequency_penalty`	float	`0`	This setting aims to control the repetition of tokens based on how often they appear in the input.
`presence_penalty`	float	`0`	Adjusts how often the model repeats specific tokens already used in the input.
`repetition_penalty`	float	`1`	Helps to reduce the repetition of tokens from the input.
`top_k`	integer	`0`	This limits the model's choice of tokens at each step, making it choose from a smaller set.
`seed`	integer	—	If specified, the inferencing will sample deterministically, such that repeated requests with the same seed and parameters should return the same result.
`min_p`	float	`0`	Represents the minimum probability for a token to be considered, relative to the probability of the most likely token.
`response_format`	map	—	Forces the model to produce specific output format.
`tool_choice`	string or object	—	Controls which (if any) tool is called by the model.
`tools`	array	—	Tool calling parameter, following OpenAI's tool calling request shape.
`logit_bias`	map	—	Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100.