Llama 3.2 1B Instruct
Neural Network
Llama 3.2 1B Instruct is a compact 1B parameter Meta language model for dialogue, summarization, and text analysis.
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 1B Instruct?
Llama 3.2 1B Instruct is a compact 1 billion parameter Meta language model. Its goal is not deep reasoning, but fast and efficient routine text work: chatting, summarizing long materials, and classifying incoming messages. Its small size ensures high response speed where request volume matters more than a single complex answer. In BotHub, the model is available without VPN or foreign cards: tokens are paid for with Russian cards as you go, without subscriptions, and do not expire. A single OpenAI-compatible API connects the model with one request, and you can switch to any of over 250 neural networks without rewriting the integration; chats are encrypted, and all models are in one window. Useful for mass summarization of emails, tickets, and reports, building first-line chat support, labeling and classifying texts before passing them to a larger model, preparing short descriptions and drafts in large volumes, or embedding an affordable text assistant directly into your product.Frequently asked questions about Llama 3.2 1B 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.
llama-3.2-1b-instruct is a compact, instruction-tuned model from the Llama family. It handles simple, high-volume tasks: short answers, rephrasing, extracting fields from documents, drafting descriptions, and sorting tickets. For streaming operations where speed and predictability matter more than deep analysis, it is a solid choice.
Maximum 54,000 tokens per response, which is about several dozen pages of text. The model's context window is 131,072 tokens, so you can upload large materials and still have room for a detailed response without cutting off mid-sentence.
A dedicated reasoning mode for this model is not noted in our data. However, you can ask it directly in the prompt to break down the task step-by-step and show its thought process — this is sufficient for simple chains. For complex calculations, switch to a reasoning model in the same window.
Function calling and strict JSON mode are not noted for this model in our data. You can request a JSON format response in the prompt, but you should verify the structure on your end. If you need guarantees, switch to a model with declared function calling via the unified OpenAI-compatible BotHub API.
You can upload images and documents: the model accepts them as input along with text; scans, diagrams, screenshots, and text files work. Audio and video are not among the supported input formats — there are separate models for them in the BotHub catalog. The response is provided in text.
The Llama 3.2 family is claimed by the developer to be multilingual, and the model works with Russian. However, this is a compact version with only 1B parameters, so the quality on long and complex texts is lower than that of larger models. Test it on your task — larger models are available nearby in the same window.