DeepSeek V3 0324
Neural Network
DeepSeek V3 0324 is a flagship DeepSeek chat model with 685B parameters on MoE architecture, available via API in BotHub.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works DeepSeek V3 0324?
DeepSeek V3 0324 is the latest iteration of the DeepSeek team's flagship chat model line: 685 billion parameters and a mixture-of-experts architecture, where only a portion of experts is activated per request. The model continues the DeepSeek V3 line and inherits its role as a universal conversationalist for text tasks. In BotHub, it works without a VPN or foreign card: you pay with Russian cards in rubles for actual tokens used, and they do not expire. Nearby in the same window are over 250 models, making it easy to switch and compare answers, while a unified OpenAI-compatible API allows you to connect DeepSeek to your services and switch models later without rewriting the integration. Chats are encrypted via AES-GCM, and companies have access to contracts, invoices, electronic document management, and an admin panel with employee limits. DeepSeek V3 0324 is most often used for dialogue assistants in support and internal services, for drafting emails, articles, and descriptions, for summarizing long documents and correspondence, for parsing raw text into structured fields, and for quickly building prototypes of multimodal products on a common API.Frequently asked questions about DeepSeek V3 0324
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 universal DeepSeek text model: it answers questions, writes and refactors code, debugs errors, works with long documents, and accepts images as input. Suitable for analytics, STEM tasks, and agent scenarios with function calling. Context is 131,072 tokens, so large projects and correspondence fit entirely.
The output limit is 147,456 tokens per response, which is a very large amount of text: documentation chapters, large code modules, or detailed analysis in full, without splitting into parts. In practice, the length depends on the request, so you should specify the desired volume directly in the prompt.
Yes, reasoning before answering is supported: the model breaks down the task step-by-step, which significantly helps with math, logic, and code debugging. For simple questions, this mode is not needed — then the answer comes immediately and faster. You can check the difference on your own tasks.
Yes, function calling and structured JSON output are supported — the model is suitable for agents, parsers, and integrations where the answer needs to be passed directly into code. In BotHub, this works via a unified OpenAI-compatible API, so you can switch to another model without rewriting the integration.
Images and documents — yes, they can be sent as input to the model: analyze a screenshot, diagram, table, or long file. Audio and video are not in the list of supported input formats; for them, BotHub has separate models available in the same window.
We do not have data on performance with specific languages, so we will not make any promises: evaluate it yourself on your tasks — correspondence, documents, code. Requests and payments in BotHub are processed from Russia without a VPN or foreign card, and there are over 250 models nearby in the same window.