Qwen3.8 Flash
Neural Network
Qwen3.8 Flash is Alibaba's multimodal reasoning model: suitable for code, agentic scenarios, and document analysis.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Qwen3.8 Flash?
Qwen3.8 Flash is a multimodal reasoning model from Alibaba. It analyzes not just text, but also images, charts, documents, and long videos, while helping with coding and agentic scenarios, including desktop interface interaction. A key strength is analyzing entire codebases rather than individual files. In BotHub, the model is accessible without a VPN or foreign card: pay with a Russian card in rubles, only for the tokens you use, which do not expire. Other neural networks are available in the same window, allowing for easy comparison, and there is a unified OpenAI-compatible API for product integrations; chats are protected by AES-GCM encryption. Qwen3.8 Flash is useful for developers for reviews, refactoring, and debugging; for analysts to extract figures from charts and reports; for product teams for agentic assistants and routine automation; and for researchers to parse voluminous documentation and long video recordings.Frequently asked questions about Qwen3.8 Flash
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.
Qwen3.8-Flash is a text model from Qwen with a context window of up to 1,000,000 tokens. It is suitable for working with long documents, code analysis and refactoring, reasoning and STEM tasks, as well as function calling scenarios. It accepts text, images, and documents as input.
In a single response, the model outputs up to 131,072 tokens—this is dozens of pages of text. This capacity is enough for a voluminous report, analyzing a large document, or an entire code module without breaking the task into parts or manually stitching response pieces together.
Yes, according to our data, a reasoning mode is supported: before providing an answer, the model consistently breaks down the task conditions. This significantly helps with math, logic, code analysis, and multi-step scenarios where it is important not to lose intermediate conclusions.
Yes, the model supports function calling and structured JSON output. It can be connected to your tools, search, and databases via the unified OpenAI-compatible BotHub API, and if necessary, you can switch to another model without rewriting the integration.
The model accepts images and documents as input: you can ask it to analyze a screenshot, diagram, table, or PDF and get a text result. There is no note in our data regarding audio and video, so plan for scenarios involving text, images, and files.
We do not have specific data on languages, so we cannot guarantee the specific quality of Russian—it is more reliable to test it with your own queries. In BotHub, the model opens without a VPN or foreign card, and payment is in rubles based on usage, so the test will take a couple of minutes.