Qwen3 30B A3B Instruct 2507
Neural Network
Qwen3 30B A3B Instruct 2507 is a Qwen MoE model for precise instruction following, available via a unified API in BotHub.
Max answer length
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Prompt cost
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How it works Qwen3 30B A3B Instruct 2507?
Qwen3 30B A3B Instruct 2507 is a language model by the Qwen team, built using a mixture of experts architecture: out of 30.5B parameters, about 3.3B are activated per request, keeping computational load moderate while maintaining a large knowledge base. The model operates without intermediate reasoning and provides immediate answers. Its strengths include precise instruction following and multilingual understanding. In BotHub, Qwen3 is accessible from Russia without a VPN or foreign card: pay with a Russian card for actual usage only, and tokens do not expire. Compare answers with over 250 other neural networks in one window, and use the unified OpenAI-compatible API to switch models without rewriting integrations. Useful for breaking down long technical tasks, formatting scattered data into JSON, drafting emails and descriptions, batch processing texts via API, or using the model as a layer in a multimodal service. For teams, we offer contracts, invoices, EDI, and an admin panel with limits.Frequently asked questions about Qwen3 30B A3B Instruct 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 an instruction-tuned Qwen model with a 131,072-token context window. It works with long texts and documents, helps write and refactor code, debug, analyze logs, solve math and STEM problems, and prepare structured summaries and drafts.
Up to 32,000 tokens per response — enough for a long article, detailed documentation, a large code module, or a detailed analysis. If the material is longer, continue the dialogue: the 131,072-token context will retain the previously generated parts.
According to our data, a separate reasoning mode is not noted for this model. However, you can ask it to break down the solution step-by-step directly in the prompt — for logic, math, and code debugging tasks, this significantly improves the quality of the result.
Yes, the model supports function calling and structured JSON output, making it easy to integrate into agents and pipelines. BotHub provides a unified OpenAI-compatible API, so you can switch to another model without rewriting your integration.
According to our data, it accepts text, images, and documents as input: you can send an interface screenshot, diagram, chart, or PDF and ask to analyze the content. Audio and video support is not noted for this model; for such tasks, choose specialized models from the catalog.
The Qwen family was trained on multilingual data and works confidently with Russian queries: summarization, rewriting, translation, and document-based Q&A. You can easily test the quality with your own task — in BotHub, access is open from Russia without a VPN or foreign card, with payment in rubles.