Alibaba Cloud: qwen3.5-omni-plus

Price, performance, capabilities, and a ready-to-use request for qwen3.5-omni-plus.
Compare models
qwen3.5-omni-plus
AvailableAlibaba CloudChat
Input / Output
$7.79 / $31.32
Context
197K
Max output
64K
Modalities
VisionChat

Getting started

  1. Create API key

    Create a key in Console, then use it with every model on the platform.

  2. Send your first request

    Copy the example for your language and run it against the endpoint.

    messagesNative (Messages API)
    POST/v1/messages
    API format:
    curl https://api.tokenlab.sh/v1/messages \
      -H "Content-Type: application/json" \
      -H "x-api-key: sk-xxx" \
      -H "anthropic-version: 2023-06-01" \
      -d '{
        "model": "qwen3.5-omni-plus",
        "max_tokens": 1024,
        "messages": [
          {"role": "user", "content": "Hello!"}
        ]
      }'

Pricing

Official price is the model maker's public baseline. TokenLab price is what you pay for this model on TokenLab.

Default

Per 1M tokens
Official price
Input $7.79 / Output $31.32 / Text Input $1.03 / Audio Input $7.79 / Image Input $1.03 / Text Output $5.88 / Audio Output $31.32
TokenLab price
Input $7.79 / Output $31.32 / Text Input $1.03 / Audio Input $7.79 / Image Input $1.03 / Text Output $5.88 / Audio Output $31.32
Discount
-

Audio on

Per 1M tokens
Official price
Input $7.79 / Output $31.32 / Text Input $1.03 / Audio Input $7.79 / Image Input $1.03 / Text Output $0.00 / Audio Output $31.32
TokenLab price
Input $7.79 / Output $31.32 / Text Input $1.03 / Audio Input $7.79 / Image Input $1.03 / Text Output $0.00 / Audio Output $31.32
Discount
-

Usage & activity

Success rate is the share of requests that completed. Latency is how long a full response takes; P95 means 95% of requests finished within that time.

Usage & availability

Last 24 hours

No data yet

Model performance
Metrics appear once privacy and data volume thresholds are met.

Data is based on aggregate user requests, excluding status checks.

Open in Console

Open qwen3.5-omni-plus in Console with a prompt ready to edit or send.

Help me try qwen3.5-omni-plus with a short message at /v1/messages. Show the reply, latency, and cost.

Use cases

Best for

Vision

Reading images, parsing documents, and answering visual questions

01

Agents and tools

Handle reasoning, support triage, tool calls, and multi-step tasks.

02

Coding

Generate, review, or debug code in the tools you already use.

03

Knowledge assistants

Build chat, search, and retrieval with a clear price and capability profile.

04

Side-by-side test

Compare response quality, latency, and price side by side.

Prompt examples

Write a concise support reply and list the assumptions behind it.

Review this API design and call out the top three integration risks.

Turn a long changelog into release notes a non-engineer would read.

This model has conditional pricing. Monthly token totals alone cannot produce a reliable estimate; use the detailed pricing for the request specification, cache, and applicable time window.

FAQ

How much does qwen3.5-omni-plus cost?

On TokenLab, qwen3.5-omni-plus costs Input $7.79 / Output $31.32 Per 1M tokens. The pricing table above shows the full breakdown. Rates depend on the billing unit, specification, and usage. Compare matching conditions in the model's detailed pricing; a single rate does not determine the total cost.

What is qwen3.5-omni-plus best for?

qwen3.5-omni-plus supports Vision. You can open it directly in Create.

How do I test qwen3.5-omni-plus?

Open qwen3.5-omni-plus in Create. A sample for /v1/messages will be ready to try.

Which endpoint should qwen3.5-omni-plus use?

Use https://api.tokenlab.sh/v1/messages for qwen3.5-omni-plus. The request example below shows the matching code shape.

Can I test qwen3.5-omni-plus before integrating it?

Yes. Open Console starts a ready draft for qwen3.5-omni-plus and keeps your prompt after sign-in, so you don’t lose context.

Which operations does qwen3.5-omni-plus support?

qwen3.5-omni-plus supports messages. Select an operation above to see its endpoint and request example.

More from Qwen Omni

Related models