Qwen3.5 Plus
Neural Network
Qwen3.5 Plus is Alibaba's multimodal model with 1M token context: accepts text, images, and video, responds with text.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 000 000 tokens
- Max answer length
- 65 536 tokens
- Reasoning effort
- low, medium, high
- Capabilities
- reasoning, function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Qwen3.5 Plus?
Qwen3.5 Plus is a large multimodal model from Alibaba that accepts text, images, and video as input and outputs text. The 1 million token context window allows you to process voluminous documentation, large code repositories, and long materials in a single request without splitting them. In BotHub, the model works without a VPN or foreign card: you pay with a Russian card in rubles only for the tokens used, with no subscription. Other neural networks are available in the same window, so you can switch and compare answers in a few clicks, and a unified OpenAI-compatible API allows you to change models for the task without rewriting the integration. Correspondence is encrypted and not saved, and companies have access to contracts, invoices, electronic document management, and an admin panel with limits. It is useful for analyzing long technical documents and reports, answering based on the entire volume, working with codebases—finding bugs, refactoring, explaining unfamiliar modules—reading diagrams, screenshots, and charts, structuring video content, and building multimodal services via API where Qwen3.5 Plus handles long-context tasks.Frequently asked questions about Qwen3.5 Plus
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
This is a text model from Qwen with a context of up to 1,000,000 tokens. It is suitable for working with code: refactoring, debugging, and analyzing large repositories. It handles long documents, analytics, STEM tasks, and logical reasoning, and can also be integrated into agent scenarios via function calling.
Up to 65,536 tokens in a single response—this is a large technical document, a large code module, or a detailed analysis of dozens of pages. If the material is larger, break the task into parts: the million-token context allows you to keep the entire project in one conversation.
Yes, the model has a reasoning mode: before the final answer, it runs a chain of thought. This helps with math, logic, code analysis, and multi-step tasks where it is important not to guess the result, but to derive and verify it sequentially.
Yes. The model supports function calling and structured JSON output, making it easy to connect to tools, databases, and external services. BotHub uses a unified OpenAI-compatible API: there is no need to rewrite the integration, just change the model name in the request.
Images and documents—yes: send a screenshot, diagram, chart, or file with a table and get a text analysis. We have no information about audio and video in our data, so it is safer to test such a file with a trial request in the BotHub interface.
The language of prompts and responses is not separately described in our data, so we will not make any promises: test the model with your task; a couple of requests will be enough for an evaluation. The BotHub interface is in Russian, payment is in rubles, and access is without a VPN or foreign card.