---
license: other
library_name: gguf
tags:
  - gguf
  - llama
  - llama-3.2
  - text-generation
  - local-llm
  - llama-cpp
  - lm-studio
  - ollama
  - 1b
pipeline_tag: text-generation
language:
  - en
base_model_relation: quantized
base_model:
  - gss1147/Llama-3.2-OctoThinker-iNano-1B
---

# Llama-3.2-OctoThinker-iNano-1B-GGUF

## Model Summary

**Llama-3.2-OctoThinker-iNano-1B-GGUF** is the GGUF quantized release of the main model:

**Main model repo:**  
https://huggingface.co/gss1147/Llama-3.2-OctoThinker-iNano-1B

This repository packages the model for efficient **local inference** in GGUF-compatible runtimes such as **llama.cpp**, **LM Studio**, and similar local tools.

## GGUF to Main Model Link

This GGUF repository corresponds to the main model repo:

**[`gss1147/Llama-3.2-OctoThinker-iNano-1B`](https://huggingface.co/gss1147/Llama-3.2-OctoThinker-iNano-1B)**

If you want the original non-GGUF model, training/merge details, tokenizer files, and main repository metadata, use the repo above.

## Available Files

This GGUF repository currently includes:

- **Q4_K_M** — 955 MB
- **Q5_K_M** — 1.09 GB
- **F16** — 3 GB

## Architecture

- **Architecture:** llama
- **Model size:** 1B params

## Intended Use

This model is intended for:

- local text generation
- assistant-style prompting
- lightweight reasoning tasks
- summarization
- simple coding help
- offline/local inference workflows

## Quantization Notes

Choose the file that best matches your hardware:

- **Q4_K_M** for smaller size and lighter RAM usage
- **Q5_K_M** for a stronger quality-to-size balance
- **F16** for the highest-fidelity file in this repo, with much higher memory requirements

## Example llama.cpp Usage

```bash
llama-cli -m /path/to/Llama-3.2-OctoThinker-iNano-1B.Q4_K_M.gguf -p "Explain recursion in Python with a simple example."