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Providers

Alibaba Anthropic Bedrock Cerebras Cohere DeepSeek Fireworks Google Groq Meta MiniMax Mistral Moonshot AI NVIDIA OpenAI Opencode Go Perplexity Thinking Machines Vertex xAI Xiaomi Z.ai

Providers

Alibaba Anthropic Bedrock Cerebras Cohere DeepSeek Fireworks Google Groq Meta MiniMax Mistral Moonshot AI NVIDIA OpenAI Opencode Go Perplexity Thinking Machines Vertex xAI Xiaomi Z.ai
Fireworks Chat Completions Retired 7 params

Fireworks GLM-5p2 API parameters

These are the API parameters modelparams.dev tracks for Fireworks GLM-5p2 on Chat Completions with an API key — the settings you send in a request. 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.

This model is retired.

After the parameter count instead — how many weights GLM-5p2 has? That's a different number, and we don't track it. Here's the difference.

Length 1 param
Parameter Type Default Description Condition
Max tokens
max_tokens 		integer (1…+∞) — Maximum number of tokens to generate in the response. —
Sampling 5 params
Parameter Type Default Description Condition
Temperature
temperature 		number (0…2 step 0.1) — Controls randomness. Lower values make outputs more focused; higher values make them more varied. —
Top P
top_p 		number (0…1 step 0.01) — Controls nucleus sampling by limiting generation to tokens within the selected cumulative probability. —
Top K
top_k 		integer (1…100) — Limits token sampling to the top K most likely next tokens. —
Presence penalty
presence_penalty 		number (-2…2 step 0.1) — Penalizes tokens that have already appeared to encourage a wider variety of content. —
Frequency penalty
frequency_penalty 		number (-2…2 step 0.1) — Penalizes tokens in proportion to how often they have already appeared. —
Output 1 param
Parameter Type Default Description Condition
Response format
response_format.type 		enum (text | json_object) — Choose plain text or force valid JSON output. —

Fireworks GLM-5p2 API parameters in brief

Fireworks GLM-5p2 on Chat Completions documents 7 API parameters, grouped by what they control:

Frequently asked questions

Which API parameters does Fireworks GLM-5p2 support?
Fireworks GLM-5p2 accepts 7 API parameters in the request body: max_tokens, temperature, top_p, top_k, presence_penalty, frequency_penalty, and more.

Resources

All Fireworks models Glossary Full catalog

GLM-5p2 — JSON

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

/api/v1/models/fireworks/glm-5p2.json 
{
  "$schema": "https://modelparams.dev/api/v1/schema.json",
  "provider": "fireworks",
  "authType": "api_key",
  "apiSurface": "openai-chat-completions",
  "model": "glm-5p2",
  "wireId": "accounts/fireworks/models/glm-5p2",
  "status": "retired",
  "params": [
    {
      "path": "max_tokens",
      "label": "Max tokens",
      "description": "Maximum number of tokens to generate in the response.",
      "group": "generation_length",
      "type": "integer",
      "range": {
        "min": 1
      }
    },
    {
      "path": "temperature",
      "label": "Temperature",
      "description": "Controls randomness. Lower values make outputs more focused; higher values make them more varied.",
      "group": "sampling",
      "type": "number",
      "range": {
        "min": 0,
        "max": 2,
        "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",
      "type": "number",
      "range": {
        "min": 0,
        "max": 1,
        "step": 0.01
      }
    },
    {
      "path": "top_k",
      "label": "Top K",
      "description": "Limits token sampling to the top K most likely next tokens.",
      "group": "sampling",
      "type": "integer",
      "range": {
        "min": 1,
        "max": 100
      }
    },
    {
      "path": "presence_penalty",
      "label": "Presence penalty",
      "description": "Penalizes tokens that have already appeared to encourage a wider variety of content.",
      "group": "sampling",
      "type": "number",
      "range": {
        "min": -2,
        "max": 2,
        "step": 0.1
      }
    },
    {
      "path": "frequency_penalty",
      "label": "Frequency penalty",
      "description": "Penalizes tokens in proportion to how often they have already appeared.",
      "group": "sampling",
      "type": "number",
      "range": {
        "min": -2,
        "max": 2,
        "step": 0.1
      }
    },
    {
      "path": "response_format.type",
      "label": "Response format",
      "description": "Choose plain text or force valid JSON output.",
      "group": "output_format",
      "type": "enum",
      "values": [
        "text",
        "json_object"
      ]
    }
  ]
}

Other Fireworks models

DeepSeek v4 Flash 0731 7 params View DeepSeek v4 Flash Vision Exp 7 params View DeepSeek v4 Pro 7 params View DeepSeek v4 Pro 0813 7 params View DeepSeek V4p1 Flash 7 params View DeepSeek V4p1 Flash 1017 7 params View Ember 1 7 params View GLM-5p3 7 params View GLM-5p3 Flash 7 params View GPT-OSS 120B 7 params View GPT-OSS 20B 7 params View Inkling 7 params View Kimi K2p6 7 params View Kimi K2p7 Code 7 params View Kimi K3 7 params View MiniMax M2p7 7 params View MiniMax M3 7 params View Muse Glimmer 30B 7 params View Muse Spark Open 7 params View Nemotron 3 Ultra Nvfp4 7 params View Nemotron Lightning 3p5 30B A3B 7 params View Qwen3p7 Plus 7 params View Qwen3p8 2p4t A95B 7 params View Qwen3p8 Max 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/models/openai/gpt-5.5.json
curl https://modelparams.dev/api/v1/models/openai/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