Qwen3 30B A3B Thinking 2507
Neural Network
Qwen3 30B A3B Thinking 2507 is a Qwen reasoning model: 30B parameters, MoE architecture, and extended thinking mode.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Qwen3 30B A3B Thinking 2507?
Qwen3 30B A3B Thinking 2507 is a reasoning model from the Qwen team with a Mixture-of-Experts architecture and 30 billion parameters, where only a subset of experts is activated at each step. It is designed for a thinking mode: internal reasoning chains are separated from the final answer, allowing the model to confidently handle long, multi-step tasks that cannot be solved in a single pass. In BotHub, it connects without a VPN or foreign card; payment is made with Russian cards in rubles based on actual usage (per token), not a subscription. All models are gathered in one window, making it easy to compare Qwen3 responses with other neural networks, and a unified OpenAI-compatible API allows switching models without rewriting integrations. Data is transmitted encrypted, and for companies, we offer contracts, invoices, and an admin panel with limits. The model helps analysts break down multi-level conditions, researchers verify hypotheses and see reasoning paths, product teams build agent scenarios via API, and engineers decompose complex tasks into intermediate steps.Frequently asked questions about Qwen3 30B A3B Thinking 2507
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 text model with a reasoning mode: it breaks down tasks step-by-step before answering. The context window is 262,144 tokens, so it can handle large documents and codebases. Suitable for code analysis, logic, STEM tasks, and function calling.
The output limit is 32,768 tokens per response. This is enough for a long article, detailed analysis, or a large code file. If you need more, break the task into parts and ask it to continue: the 262,144-token context allows it to maintain the entire conversation.
Yes, reasoning before answering is a confirmed capability of this model: before providing a result, it runs through a chain of thought. This significantly helps with math, logic, code debugging, and multi-step tasks where not just the answer, but the correct path to it, is important.
Yes, the model supports function calling and structured JSON output. You can connect it to your tools, databases, and services, and receive answers in a predefined schema. In BotHub, this works via a unified OpenAI-compatible API — you can switch models without rewriting integrations.
You can upload images and documents: the model accepts them as input and responds with text — it can analyze screenshots, diagrams, contracts, or PDFs with tables. There is no information about audio or video in our data, so for audio processing or video analysis, please choose a specialized model from the catalog.
Our data does not specify the language of prompts and responses, so we cannot make specific promises. Test it with your own task: in BotHub, the model is available in the same window as others, so it is easy to send the same request to several models and compare the results.