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NVIDIA 7 params

NVIDIA DeepSeek v4 Flash 0731 API parameters

These are the API parameters modelparams.dev tracks for NVIDIA DeepSeek v4 Flash 0731 — 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 DeepSeek v4 Flash 0731 has? That's a different number, and we don't track it. Here's the difference.

Length 2 params
Parameter Type Default Description Condition
Max tokens
max_tokens
integer (1…16384) 4096 Maximum number of tokens to generate. Generation stops when this limit is reached.
Stop
stop
string A string or list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.
Sampling 5 params
Parameter Type Default Description Condition
Temperature
temperature
number (0…1) 0.6 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.
Frequency penalty
frequency_penalty
number (-2…2) 0 Penalizes new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
Presence penalty
presence_penalty
number (-2…2) 0 Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
Seed
seed
integer (0…18446744073709552000) 0 Best-effort deterministic sampling seed. Changing the seed produces a different response with similar characteristics. Fix the seed to reproduce results.

NVIDIA DeepSeek v4 Flash 0731 API parameters in brief

NVIDIA DeepSeek v4 Flash 0731 documents 7 API parameters, grouped by what they control:

Frequently asked questions

Which API parameters does NVIDIA DeepSeek v4 Flash 0731 support?
NVIDIA DeepSeek v4 Flash 0731 accepts 7 API parameters in the request body: temperature, top_p, max_tokens, frequency_penalty, presence_penalty, seed, and more.
What is the default temperature for NVIDIA DeepSeek v4 Flash 0731?
The default temperature for NVIDIA DeepSeek v4 Flash 0731 is 0.6, within a valid range of 0 to 1.
What is the default top_p for NVIDIA DeepSeek v4 Flash 0731?
The default top_p for NVIDIA DeepSeek v4 Flash 0731 is 0.95, with a maximum of 1.
What is the default max_tokens for NVIDIA DeepSeek v4 Flash 0731?
The default max_tokens for NVIDIA DeepSeek v4 Flash 0731 is 4096, within a valid range of 1 to 16384.

Resources

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DeepSeek v4 Flash 0731 — 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",
  "model": "deepseek-v4-flash-0731",
  "wireId": "deepseek-ai/deepseek-v4-flash-0731",
  "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": 0.6,
      "range": {
        "min": 0,
        "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": 4096,
      "range": {
        "min": 1,
        "max": 16384
      }
    },
    {
      "path": "frequency_penalty",
      "label": "Frequency penalty",
      "description": "Penalizes new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.",
      "group": "sampling",
      "type": "number",
      "default": 0,
      "range": {
        "min": -2,
        "max": 2
      }
    },
    {
      "path": "presence_penalty",
      "label": "Presence penalty",
      "description": "Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.",
      "group": "sampling",
      "type": "number",
      "default": 0,
      "range": {
        "min": -2,
        "max": 2
      }
    },
    {
      "path": "seed",
      "label": "Seed",
      "description": "Best-effort deterministic sampling seed. Changing the seed produces a different response with similar characteristics. Fix the seed to reproduce results.",
      "group": "sampling",
      "type": "integer",
      "default": 0,
      "range": {
        "min": 0,
        "max": 18446744073709552000
      }
    },
    {
      "path": "stop",
      "label": "Stop",
      "description": "A string or list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.",
      "group": "generation_length",
      "type": "string"
    }
  ]
}

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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

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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