DeepSeek V3
Neural Network
DeepSeek V3 is a language model from the DeepSeek team, used for coding tasks and precise instruction following.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works DeepSeek V3?
DeepSeek V3 is a language model from the DeepSeek team that builds on the strengths of previous versions: instruction following and coding. It is pre-trained on nearly 15 trillion tokens. Connecting via BotHub is easier than direct access: no VPN or foreign card required, payment is in rubles via Russian cards, and you only pay for tokens used, with no expiration on your balance. Access over 250 models in one window to compare answers, and use a single OpenAI-compatible API for your services, so switching models doesn't require rewriting integrations. For developers, DeepSeek V3 helps analyze unfamiliar code, write functions and tests, and debug. For analysts and product teams, it summarizes long documents and correspondence. For editors and marketers, it drafts content from brief prompts. Companies benefit from contracts, invoices, electronic document management, and an admin panel with employee limits, while traffic is encrypted via AES-GCM and chats are not stored.Frequently asked questions about DeepSeek V3
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.
It is a universal text model: dialogue and correspondence, coding, explanation and refactoring, document and image analysis, analytics and summaries. The 64,000-token context window allows you to handle long conversations, technical specifications, or multiple files at once.
Up to 16,000 tokens per response — enough for a long article, detailed analysis, or a large code module. If the material is longer, split the task and ask it to continue: in BotHub, you pay only for tokens used, and they do not expire.
A separate reasoning mode is not explicitly noted in our data, but the model performs well with step-by-step analysis if requested directly in the prompt: break down the logic, verify hypotheses, and then provide the final conclusion.
Yes, the model supports function calling and structured JSON output — convenient for agents, service integrations, and automation. It connects via the unified OpenAI-compatible BotHub API, so you can switch models without rewriting integrations.
It accepts text, images, and documents as input: you can ask it to analyze a screenshot, diagram, contract, or report and get a text response. Audio and video capabilities are not supported — BotHub has separate specialized models for those.
DeepSeek models were trained on multilingual data and handle Russian-language tasks well in practice. The easiest way to check is by testing: run your prompt through deepseek-chat and neighboring models in the BotHub window and compare the results. Access from Russia without VPN, payment via Russian cards.