modelparams.dev
Alibaba Chat Completions Retired 5 params

Alibaba Qwen Vl Plus API parameters

These are the API parameters modelparams.dev tracks for Alibaba Qwen Vl Plus 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.

This model is retired.

After the parameter count instead — how many weights Qwen Vl Plus 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 true Controls Qwen3 thinking mode when using OpenAI-compatible clients that pass provider-specific extra body fields. —

Alibaba Qwen Vl Plus API parameters in brief

Alibaba Qwen Vl Plus on Chat Completions documents 5 API parameters, grouped by what they control:

Frequently asked questions

Which API parameters does Alibaba Qwen Vl Plus support?
Alibaba Qwen Vl Plus 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

All Alibaba models Glossary Full catalog

Qwen Vl Plus — 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",
  "apiSurface": "openai-chat-completions",
  "model": "qwen-vl-plus",
  "status": "retired",
  "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": true
    }
  ]
}

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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