modelparams.dev
NVIDIA Chat Completions 5 params

NVIDIA Nemotron 3.5 Super Vl 120B A12B API parameters

These are the API parameters modelparams.dev tracks for NVIDIA Nemotron 3.5 Super Vl 120B A12B 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.

After the parameter count instead — how many weights Nemotron 3.5 Super Vl 120B A12B 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…32768) 16384 Maximum number of tokens to generate. Generation stops when this limit is reached. —
Sampling 2 params
Parameter Type Default Description Condition
Temperature
temperature
number (-∞…1) 1 Controls randomness. Lower values make outputs more focused; higher values make them more varied. Not recommended to modify both temperature and top_p in the same call. —
Top P
top_p
number (-∞…1) 0.95 Controls nucleus sampling by limiting generation to tokens within the selected cumulative probability. Not recommended to modify both temperature and top_p in the same call. —
Reasoning 2 params
Parameter Type Default Description Condition
Reasoning effort
reasoning_effort
enum (none | low | high) "high" Controls the reasoning mode. 'none' disables reasoning tokens, 'low' enables low-effort reasoning, and 'high' enables full reasoning. —
Reasoning budget
reasoning_budget
integer (-1…32768) 16384 Maximum number of tokens the model may use for internal reasoning before being forced to end the reasoning trace. Use -1 to disable budget enforcement. —

NVIDIA Nemotron 3.5 Super Vl 120B A12B API parameters in brief

NVIDIA Nemotron 3.5 Super Vl 120B A12B on Chat Completions documents 5 API parameters, grouped by what they control:

Frequently asked questions

Which API parameters does NVIDIA Nemotron 3.5 Super Vl 120B A12B support?
NVIDIA Nemotron 3.5 Super Vl 120B A12B accepts 5 API parameters in the request body: temperature, top_p, max_tokens, reasoning_effort, reasoning_budget.
What is the default temperature for NVIDIA Nemotron 3.5 Super Vl 120B A12B?
The default temperature for NVIDIA Nemotron 3.5 Super Vl 120B A12B is 1, with a maximum of 1.
What is the default top_p for NVIDIA Nemotron 3.5 Super Vl 120B A12B?
The default top_p for NVIDIA Nemotron 3.5 Super Vl 120B A12B is 0.95, with a maximum of 1.
What is the default max_tokens for NVIDIA Nemotron 3.5 Super Vl 120B A12B?
The default max_tokens for NVIDIA Nemotron 3.5 Super Vl 120B A12B is 16384, within a valid range of 1 to 32768.

Resources

All NVIDIA models Glossary Full catalog

Nemotron 3.5 Super Vl 120B A12B — JSON

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

{
  "$schema": "https://modelparams.dev/api/v1/schema.json",
  "provider": "nvidia",
  "authType": "api_key",
  "apiSurface": "openai-chat-completions",
  "model": "nemotron-3.5-super-vl-120b-a12b",
  "wireId": "nvidia/nemotron-3.5-super-vl-120b-a12b",
  "params": [
    {
      "path": "temperature",
      "label": "Temperature",
      "description": "Controls randomness. Lower values make outputs more focused; higher values make them more varied. Not recommended to modify both temperature and top_p in the same call.",
      "group": "sampling",
      "type": "number",
      "default": 1,
      "range": {
        "max": 1
      }
    },
    {
      "path": "top_p",
      "label": "Top P",
      "description": "Controls nucleus sampling by limiting generation to tokens within the selected cumulative probability. Not recommended to modify both temperature and top_p in the same call.",
      "group": "sampling",
      "type": "number",
      "default": 0.95,
      "range": {
        "max": 1
      }
    },
    {
      "path": "max_tokens",
      "label": "Max tokens",
      "description": "Maximum number of tokens to generate. Generation stops when this limit is reached.",
      "group": "generation_length",
      "type": "integer",
      "default": 16384,
      "range": {
        "min": 1,
        "max": 32768
      }
    },
    {
      "path": "reasoning_effort",
      "label": "Reasoning effort",
      "description": "Controls the reasoning mode. 'none' disables reasoning tokens, 'low' enables low-effort reasoning, and 'high' enables full reasoning.",
      "group": "reasoning",
      "type": "enum",
      "default": "high",
      "values": [
        "none",
        "low",
        "high"
      ]
    },
    {
      "path": "reasoning_budget",
      "label": "Reasoning budget",
      "description": "Maximum number of tokens the model may use for internal reasoning before being forced to end the reasoning trace. Use -1 to disable budget enforcement.",
      "group": "reasoning",
      "type": "integer",
      "default": 16384,
      "range": {
        "min": -1,
        "max": 32768
      }
    }
  ]
}

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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