modelparams.dev
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Providers

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

Providers

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

Moonshot AI Moonshot v1 8K parameters

These are the parameters modelparams.dev tracks for Moonshot AI Moonshot v1 8K. 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 2 params
Parameter Type Default Description Condition
Max completion tokens
max_completion_tokens 		integer (1…+∞) — Maximum number of tokens to generate in the chat completion. —
Number of completions
n 		integer (1…5) 1 How many chat completion choices to generate for the request. —
Sampling 4 params
Parameter Type Default Description Condition
Temperature
temperature 		number (0…1 step 0.1) 0.3 Controls randomness. Lower values make outputs more focused; higher values make them more varied. —
Top P
top_p 		number (0…1 step 0.01) 1 Controls nucleus sampling by limiting generation to tokens within the selected cumulative probability. —
Presence penalty
presence_penalty 		number (-2…2 step 0.1) 0 Penalizes tokens that have already appeared, encouraging the model to talk about new topics. —
Frequency penalty
frequency_penalty 		number (-2…2 step 0.1) 0 Penalizes tokens by how often they have appeared, reducing verbatim repetition. —
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. —

Moonshot AI Moonshot v1 8K API parameters in brief

Moonshot AI Moonshot v1 8K documents 7 API parameters, grouped by what they control:

Frequently asked questions

How many parameters does Moonshot AI Moonshot v1 8K accept?
Moonshot AI Moonshot v1 8K accepts 7 API parameters: max_completion_tokens, temperature, top_p, n, presence_penalty, frequency_penalty, and more.
What is the default temperature for Moonshot AI Moonshot v1 8K?
The default temperature for Moonshot AI Moonshot v1 8K is 0.3, within a valid range of 0 to 1.
What is the default top_p for Moonshot AI Moonshot v1 8K?
The default top_p for Moonshot AI Moonshot v1 8K is 1, within a valid range of 0 to 1.

Resources

All Moonshot AI models Glossary Full catalog

Moonshot v1 8K — JSON

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

/api/v1/models/moonshot/moonshot-v1-8k.json 
{
  "$schema": "https://modelparams.dev/api/v1/schema.json",
  "provider": "moonshot",
  "authType": "api_key",
  "model": "moonshot-v1-8k",
  "params": [
    {
      "path": "max_completion_tokens",
      "label": "Max tokens",
      "description": "Maximum number of tokens to generate in the chat completion.",
      "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",
      "default": 0.3,
      "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",
      "type": "number",
      "default": 1,
      "range": {
        "min": 0,
        "max": 1,
        "step": 0.01
      }
    },
    {
      "path": "n",
      "label": "Number of completions",
      "description": "How many chat completion choices to generate for the request.",
      "group": "generation_length",
      "type": "integer",
      "default": 1,
      "range": {
        "min": 1,
        "max": 5
      }
    },
    {
      "path": "presence_penalty",
      "label": "Presence penalty",
      "description": "Penalizes tokens that have already appeared, encouraging the model to talk about new topics.",
      "group": "sampling",
      "type": "number",
      "default": 0,
      "range": {
        "min": -2,
        "max": 2,
        "step": 0.1
      }
    },
    {
      "path": "frequency_penalty",
      "label": "Frequency penalty",
      "description": "Penalizes tokens by how often they have appeared, reducing verbatim repetition.",
      "group": "sampling",
      "type": "number",
      "default": 0,
      "range": {
        "min": -2,
        "max": 2,
        "step": 0.1
      }
    },
    {
      "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 Moonshot AI models

Kimi K2.5 3 params View Kimi K2.6 3 params View Kimi K2.6 Subscription 3 params View Kimi K2.7 Code Subscription 2 params View Kimi K2.7 Code Highspeed Subscription 2 params View Moonshot v1 128K 7 params View Moonshot v1 32K 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