modelparams.dev
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Providers

Alibaba Anthropic Cohere DeepSeek Google Meta MiniMax Mistral Moonshot AI Nvidia OpenAI Perplexity Thinking Machines xAI Xiaomi Z.ai

Providers

Alibaba Anthropic Cohere DeepSeek Google Meta MiniMax Mistral Moonshot AI Nvidia OpenAI Perplexity Thinking Machines xAI Xiaomi Z.ai
Z.ai 7 params

Z.ai GLM-5.2 parameters

These are the parameters modelparams.dev tracks for Z.ai GLM-5.2. Each row gives the type, default, valid range or values, and the conditions that gate it. It's the same data the JSON API serves.

Length 1 param
Parameter Type Default Description Condition
Max tokens
max_tokens 		integer (1…131072) 65536 Maximum number of tokens to generate in the response. —
Sampling 3 params
Parameter Type Default Description Condition
Temperature
temperature 		number (0…1 step 0.1) 1 Controls randomness. Lower values make outputs more focused; higher values make them more varied.
Not when do_sample = false
Top P
top_p 		number (0.01…1 step 0.01) 0.95 Controls nucleus sampling by limiting generation to tokens within the selected cumulative probability.
Not when do_sample = false
Do sample
do_sample 		boolean true When false, the model uses greedy decoding and ignores temperature and top_p. —
Reasoning 2 params
Parameter Type Default Description Condition
Thinking mode
thinking.type 		enum (enabled | disabled) "enabled" Toggles the model's extended reasoning before it produces the final answer. —
Reasoning effort
reasoning_effort 		enum (none | minimal | low | medium | high | xhigh | max) "max" Controls how much reasoning effort GLM-5.2 spends when thinking is enabled.
Only when thinking.type = "enabled"
Output 1 param
Parameter Type Default Description Condition
Response format
response_format.type 		enum (text | json_object) "text" Forces the response into plain text or a JSON object. —

Z.ai GLM-5.2 API parameters in brief

Z.ai GLM-5.2 documents 7 API parameters, grouped by what they control:

Frequently asked questions

How many parameters does Z.ai GLM-5.2 accept?
Z.ai GLM-5.2 accepts 7 API parameters: max_tokens, temperature, top_p, do_sample, thinking.type, reasoning_effort, and more.
What is the default temperature for Z.ai GLM-5.2?
The default temperature for Z.ai GLM-5.2 is 1, within a valid range of 0 to 1.
What is the default top_p for Z.ai GLM-5.2?
The default top_p for Z.ai GLM-5.2 is 0.95, within a valid range of 0.01 to 1.
What is the default max_tokens for Z.ai GLM-5.2?
The default max_tokens for Z.ai GLM-5.2 is 65536, within a valid range of 1 to 131072.

Resources

All Z.ai models Glossary Full catalog

GLM-5.2 — JSON

The full model definition as served by the API. Copy it or open the endpoint directly.

/api/v1/models/z-ai/glm-5.2.json 
{
  "$schema": "https://modelparams.dev/api/v1/schema.json",
  "provider": "z-ai",
  "authType": "api_key",
  "model": "glm-5.2",
  "params": [
    {
      "path": "max_tokens",
      "label": "Max tokens",
      "description": "Maximum number of tokens to generate in the response.",
      "group": "generation_length",
      "type": "integer",
      "default": 65536,
      "range": {
        "min": 1,
        "max": 131072
      }
    },
    {
      "path": "temperature",
      "label": "Temperature",
      "description": "Controls randomness. Lower values make outputs more focused; higher values make them more varied.",
      "group": "sampling",
      "applicability": {
        "except": {
          "do_sample": false
        }
      },
      "type": "number",
      "default": 1,
      "range": {
        "min": 0,
        "max": 1,
        "step": 0.1
      }
    },
    {
      "path": "top_p",
      "label": "Top P",
      "description": "Controls nucleus sampling by limiting generation to tokens within the selected cumulative probability.",
      "group": "sampling",
      "applicability": {
        "except": {
          "do_sample": false
        }
      },
      "type": "number",
      "default": 0.95,
      "range": {
        "min": 0.01,
        "max": 1,
        "step": 0.01
      }
    },
    {
      "path": "do_sample",
      "label": "Do sample",
      "description": "When false, the model uses greedy decoding and ignores temperature and top_p.",
      "group": "sampling",
      "type": "boolean",
      "default": true
    },
    {
      "path": "thinking.type",
      "label": "Thinking mode",
      "description": "Toggles the model's extended reasoning before it produces the final answer.",
      "group": "reasoning",
      "type": "enum",
      "default": "enabled",
      "values": [
        "enabled",
        "disabled"
      ]
    },
    {
      "path": "reasoning_effort",
      "label": "Reasoning effort",
      "description": "Controls how much reasoning effort GLM-5.2 spends when thinking is enabled.",
      "group": "reasoning",
      "applicability": {
        "only": {
          "thinking.type": "enabled"
        }
      },
      "type": "enum",
      "default": "max",
      "values": [
        "none",
        "minimal",
        "low",
        "medium",
        "high",
        "xhigh",
        "max"
      ]
    },
    {
      "path": "response_format.type",
      "label": "Response format",
      "description": "Forces the response into plain text or a JSON object.",
      "group": "output_format",
      "type": "enum",
      "default": "text",
      "values": [
        "text",
        "json_object"
      ]
    }
  ]
}

Other Z.ai models

GLM-4.5 6 params View GLM-4.5 Subscription 6 params View GLM-4.5-Air 6 params View GLM-4.5-Air Subscription 6 params View GLM-4.5-AirX 6 params View GLM-4.5-Flash 6 params View GLM-4.5-X 6 params View GLM-4.6 6 params View GLM-4.6 Subscription 6 params View GLM-4.7 6 params View GLM-4.7 Subscription 6 params View GLM-4.7-Flash 6 params View GLM-4.7-FlashX 6 params View GLM-5 6 params View GLM-5 Subscription 6 params View GLM-5-Turbo 6 params View GLM-5-Turbo Subscription 6 params View GLM-5.1 6 params View GLM-5.1 Subscription 6 params View GLM-5.2 Subscription 7 params View

How to use

Building with an AI agent? Hit Copy to grab this whole guide as Markdown and paste it in — or point your agent straight at /llms.txt.

modelparams.dev is an open, community-maintained catalog of model parameters. Each entry shows the knobs you can turn — type, default, range, and the conditions that gate it.

The same model accessed via an API key and via a subscription usually exposes a different set of parameters. We list both as separate entries so the data stays honest.

Catalog API

The full catalog is static JSON, CORS-enabled, served from the edge.

curl https://modelparams.dev/api/v1/models.json

Each entry is keyed by provider/model for API-key variants; subscription variants append -subscription.

If you only need the params for one model contract, use the providerless endpoint. Subscription contracts are model slugs with -subscription. 

curl https://modelparams.dev/api/v1/params/gpt-5.5.json
curl https://modelparams.dev/api/v1/params/gpt-5.5-subscription.json

Single model

curl https://modelparams.dev/api/v1/models/anthropic/claude-opus-4-7.json
curl https://modelparams.dev/api/v1/models/anthropic/claude-opus-4-7-subscription.json

JSON Schema

Every entry validates against a JSON Schema you can use in your editor or pipeline. 

curl https://modelparams.dev/api/v1/schema.json

Add this header to any YAML you author for autocomplete in VS Code: 

# yaml-language-server: $schema=https://modelparams.dev/api/v1/schema.json

Logos

Provider logos are available at /assets/logos/{provider}.svg where {provider} is the provider slug. They use currentColor so they inherit your text color. 

curl https://modelparams.dev/assets/logos/anthropic.svg

Logos are sourced from the models.dev repo (MIT) and used under nominative fair use.

Contribute

The data lives in YAML under models/{provider}/{model}-{auth}.yaml in the GitHub repo. Open a PR; CI validates against the schema and rebuilds.

Edit on GitHub MIT licensed