Llama 3.2 3B Instruct
Neural Network
Llama 3.2 3B Instruct is a compact Meta language model for dialogue, reasoning, and summarization, available on BotHub.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Llama 3.2 3B Instruct?
Llama 3.2 3B Instruct is a compact 3-billion parameter language model by Meta, built on a modern transformer architecture and fine-tuned for dialogue, reasoning, and text summarization. Multilingualism is built into the model, and its small size makes it convenient where response speed and processing volume are critical. On BotHub, it is accessible without a VPN or foreign card: pay with a Russian card in rubles only for what you actually use, and unused tokens do not expire. Over 250 models are available in one window, allowing you to switch between them to compare responses to the same prompt. A unified OpenAI-compatible API lets you change models in your product without rewriting the integration. Chats are encrypted via AES-GCM, and data is not saved. It is suitable for chatbots and first-line support assistants, summarizing long conversations, reports, and articles into short summaries, drafting large text arrays before passing them to a heavier model, and embedding into services requiring a fast language layer.Frequently asked questions about Llama 3.2 3B Instruct
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.
The model works with text and documents: summarization, rewriting, answering based on uploaded files, data extraction, drafting, and simple code. It accepts images as input and supports function calling, making it easy to integrate into services. The 131,072-token context window allows you to keep long materials in the dialogue entirely.
Up to 117,964 tokens in a single response—that's the volume of a small book. Enough for a detailed document analysis, a large code fragment, or a long instruction. In practice, the response is usually shorter: the model writes as much as the task and your prompt require.
A separate step-by-step reasoning mode is not noted for this model in our data, so the response comes immediately. If you need a chain of thought, ask the model to break down the task step-by-step in your prompt—then the thought process will be visible directly in the response text.
Yes, both. The model supports function calling and structured JSON output, so you can connect it to your tools, databases, and external APIs. On BotHub, this works via a unified OpenAI-compatible API—you won't have to rewrite your integration.
Images and documents—yes, you can send them to the model along with your question. Audio and video are not listed in the input formats, so for voiceovers or recording analysis, select a specialized model in the same BotHub window and switch to it in one move.
The working language is not separately noted in our data, so we won't make any promises—test it on your task. It's easy to do: on BotHub, you pay per token, without a subscription, and other models are available in the same window for comparison.