modelparams.dev

Alibaba Qwen3 30B A3B Instruct 2507 API parameters

These are the API parameters modelparams.dev tracks for Alibaba Qwen3 30B A3B Instruct 2507 — 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 Qwen3 30B A3B Instruct 2507 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 output tokens the model may generate. —
Sampling 3 params
Parameter Type Default Description Condition
Temperature
temperature
number (0…1.9 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
extra_body.top_k
integer (1…+∞) 20 Limits generation to the selected number of highest-probability tokens. —
Reasoning 1 param
Parameter Type Default Description Condition
Enable thinking
extra_body.chat_template_kwargs.enable_thinking
boolean false Controls Qwen3 thinking mode when using OpenAI-compatible clients that pass provider-specific extra body fields. —

Alibaba Qwen3 30B A3B Instruct 2507 API parameters in brief

Alibaba Qwen3 30B A3B Instruct 2507 documents 5 API parameters, grouped by what they control:

Frequently asked questions

Which API parameters does Alibaba Qwen3 30B A3B Instruct 2507 support?
Alibaba Qwen3 30B A3B Instruct 2507 accepts 5 API parameters in the request body: max_tokens, temperature, top_p, extra_body.top_k, extra_body.chat_template_kwargs.enable_thinking.

Resources

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Qwen3 30B A3B Instruct 2507 — 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": "alibaba",
  "authType": "api_key",
  "model": "qwen3-30b-a3b-instruct-2507",
  "params": [
    {
      "path": "max_tokens",
      "label": "Max tokens",
      "description": "Maximum number of output tokens the model may generate.",
      "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": 1.9,
        "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": "extra_body.top_k",
      "label": "Top K",
      "description": "Limits generation to the selected number of highest-probability tokens.",
      "group": "sampling",
      "type": "integer",
      "default": 20,
      "range": {
        "min": 1
      }
    },
    {
      "path": "extra_body.chat_template_kwargs.enable_thinking",
      "label": "Enable thinking",
      "description": "Controls Qwen3 thinking mode when using OpenAI-compatible clients that pass provider-specific extra body fields.",
      "group": "reasoning",
      "type": "boolean",
      "default": false
    }
  ]
}

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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