modelparams.dev
API GitHub

Providers

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

Providers

Alibaba Anthropic Cohere DeepSeek Google Meta MiniMax Mistral Moonshot AI Nvidia OpenAI Perplexity xAI Z.ai
Nvidia 4 params

Nvidia Gliner Pii parameters

These are the parameters modelparams.dev tracks for Nvidia Gliner Pii. 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.

Sampling 1 param
Parameter Type Default Description Condition
Threshold
threshold 		number (0…1) 0.5 Confidence threshold for entity detection. Lower values detect more entities but may include false positives. —
Metadata 3 params
Parameter Type Default Description Condition
Chunk length
chunk_length 		integer (1…2048) 384 Context window size for processing. Longer texts are automatically split into chunks with overlap for complete coverage. Must be greater than overlap. —
Overlap
overlap 		integer (0…512) 128 Token overlap between chunks to prevent entity clipping. Must be less than chunk_length. —
Flat NER
flat_ner 		boolean false When true, prevents overlapping entity spans. When false, may return nested entities such as both a full name and its constituent first name. —

Resources

All Nvidia models Glossary Full catalog

Gliner Pii — JSON

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

/api/v1/models/nvidia/gliner-pii.json 
{
  "$schema": "https://modelparams.dev/api/v1/schema.json",
  "provider": "nvidia",
  "authType": "api_key",
  "model": "gliner-pii",
  "params": [
    {
      "path": "threshold",
      "label": "Threshold",
      "description": "Confidence threshold for entity detection. Lower values detect more entities but may include false positives.",
      "group": "sampling",
      "type": "number",
      "default": 0.5,
      "range": {
        "min": 0,
        "max": 1
      }
    },
    {
      "path": "chunk_length",
      "label": "Chunk length",
      "description": "Context window size for processing. Longer texts are automatically split into chunks with overlap for complete coverage. Must be greater than overlap.",
      "group": "provider_metadata",
      "type": "integer",
      "default": 384,
      "range": {
        "min": 1,
        "max": 2048
      }
    },
    {
      "path": "overlap",
      "label": "Overlap",
      "description": "Token overlap between chunks to prevent entity clipping. Must be less than chunk_length.",
      "group": "provider_metadata",
      "type": "integer",
      "default": 128,
      "range": {
        "min": 0,
        "max": 512
      }
    },
    {
      "path": "flat_ner",
      "label": "Flat NER",
      "description": "When true, prevents overlapping entity spans. When false, may return nested entities such as both a full name and its constituent first name.",
      "group": "provider_metadata",
      "type": "boolean",
      "default": false
    }
  ]
}

Other Nvidia models

Llama 3.1 Nemoguard 8b Topic Control 6 params View Llama 3.1 Nemotron Nano 8b V1 7 params View Llama 3.1 Nemotron Safety Guard 8b V3 1 param View Llama 3.1 Nemotron Ultra 253b V1 7 params View Llama 3.3 Nemotron Super 49b V1 7 params View Llama 3.3 Nemotron Super 49b V1.5 7 params View Nemoguard Jailbreak Detect 0 params View Nemotron 3 Nano 30b A3b 5 params View Nemotron 3 Super 120b A12b 7 params View Nemotron 3 Ultra 550b A55b 7 params View Nemotron Content Safety Reasoning 4b 5 params View Nemotron Mini 4b Instruct 6 params View Riva Translate 4b Instruct V1.1 6 params View Usdcode Llama 3.1 70b Instruct 4 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 LLM 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