Qwen3 Coder 30B A3B Instruct
Neural Network
Qwen3 Coder 30B A3B Instruct is a Qwen model for code: generation, repository understanding, and tool calling.
Max answer length
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Context size
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Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Qwen3 Coder 30B A3B Instruct?
Qwen3 Coder 30B A3B Instruct is a Qwen model with a Mixture-of-Experts architecture: out of 30.5 billion parameters and 128 experts, only eight are activated at each step, making this large model efficient. It has a narrow, applied profile: code generation, understanding repository-scale projects, and agentic work with external tool calling, where the model selects the necessary function and continues the chain of actions. In BotHub, it connects without a VPN or foreign card; payment is made with Russian cards in rubles based on actual usage, and unused tokens do not expire. A unified OpenAI-compatible API means you can switch from Qwen3 Coder to any of the 250+ other models without rewriting your integration, while chats are encrypted and not saved. It is convenient for developers to write and refactor modules, analyze unfamiliar code, and review changes; for teams to build agents that interact with tools and external APIs; for data engineers to write scripts and autotests; and for companies to work under contract with invoicing, electronic document management, an admin panel, and limits.Frequently asked questions about Qwen3 Coder 30B A3B Instruct
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 Qwen model focused on working with code: writing functions, refactoring, debugging, and explaining others' solutions. A 262,144-token context allows you to upload a large project or documentation in its entirety, and you can input documents and images.
In a single response, the model can output up to 235,929 tokens — enough for a voluminous module, a set of tests, or a detailed analysis with comments. If the response cuts off, just ask it to continue: the 262,144-token context will preserve the entire previous conversation.
A separate reasoning mode is not noted in our data, so we will not promise it. In practice, it helps to ask the model to break down the task step-by-step before writing code: describe the input data, edge cases, and plan, and then write the implementation.
Yes, function calling and structured JSON output are supported. You describe a set of tools, and the model returns a correct call with arguments — convenient for agents and automation. Through the unified OpenAI-compatible BotHub API, such integration connects without rewriting code.
Images and documents — yes: you can attach a screenshot with an error, an interface diagram, or a technical specification and ask it to analyze them. Audio and video as input formats are not noted in our data. The model responds with text and code.
We do not have data on prompt and response languages, so we will not make exact promises — test it on your task, it's quick. The BotHub interface is in Russian, access from Russia is available without a VPN or foreign card, and payment is made with Russian cards in rubles.