Qwen Plus
Neural Network
Qwen Plus is an Alibaba language model based on Qwen2.5 with 131K context for working with code and long texts.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Qwen Plus?
Qwen Plus is built on the base Qwen2.5 model and is designed for a balanced ratio of response quality, generation speed, and token costs. The 131K token context window allows you to work with entire voluminous materials: multi-page reports, documentation, long correspondence, or a large code module, without breaking them into fragments. Through BotHub, the model is available without a VPN or foreign card; payment is made with Russian cards in rubles based on actual tokens used, not by subscription. Over 250 other neural networks are available in the same window, so you can compare responses or switch to another model without rewriting the integration: the unified OpenAI-compatible API remains the same. Correspondence is encrypted, and companies have access to contracts, invoices, and an admin panel with limits. Developers use Qwen Plus for code generation and refactoring, stack trace analysis, and reviewing large modules. For analysts, the model helps extract insights from long documents; for support, it helps prepare answers based on a knowledge base; and for product teams, it helps prototype scenarios with high request volume where the cost of each request is important.Frequently asked questions about Qwen 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.
qwen-plus is a text model from Qwen with a 131,072 token context. It is suitable for working with long documents and code: refactoring, debugging, explaining third-party logic, analytics, and summarizing reports. It accepts not only text but also images and documents as input, and can call external functions.
In a single response, the model outputs up to 32,768 tokens — this is a voluminous article, a large section of documentation, or several entire code files. If the material doesn't fit, just ask it to continue: the question and answer remain in the general 131,072 token window.
A separate reasoning mode is not noted in our data for qwen-plus, so we will not promise it. However, a step-by-step breakdown is easy to obtain with a prompt: ask it to break the task into steps, check the solution process, and only then provide the result — the long context allows for this.
Yes, this is a confirmed capability: the model supports function calling and structured JSON output. Describe the tool schema, and it will select the necessary call with arguments itself — convenient for agents, bots, and parsing. Through the unified OpenAI-compatible BotHub API, you won't have to rewrite the connection.
Images and documents — yes: send a screenshot, diagram, table, or file and ask it to analyze the content. Audio and video are not listed among the supported inputs for this model — there are separate solutions for them in the BotHub catalog. You receive text as output.
There are no notes about query and response languages in our data, so we won't make exact promises — it's easier to check with your own real task in a couple of queries. BotHub itself works entirely in Russian: interface, payment with Russian cards in rubles, access without VPN and foreign cards.