Llama 3.2 1B Instruct Q8 0 Alternatives

The Llama 3.2 1B Instruct Q4_K_M is a quantized GGUF version of a text generation model hosted on Hugging Face. It belongs to the class of foundation models and carries tags for conversational use, Llama architecture, and llama.cpp compatibility. The repository is maintained under the hugging-quants organization and includes the file llama-3.2-1b-instruct-q4_k_m.gguf. It is marked as quantized, with a total file size of 807690656 bytes. The model card lists support for eight languages and references the original Meta Llama 3.2 1B Instruct base along with PyTorch and GGUF formats. A chat template is defined in the repository data using special tokens such as bos_token, eos_token, and structured role headers for assistant and user messages. This enables direct use in compatible inference engines without additional conversion. The page indicates four discussions, two of which are closed. No pricing, licensing terms, or specific target audience beyond the model tags are stated in the repository metadata.

This repository contains GGUF quantized files of Meta's Llama 3.2 3B Instruct model, maintained by the LM Studio community. It supports tool calling, system prompts, and efficient local execution using tools like llama.cpp. The model is ideal for developers seeking lightweight, locally runnable instruction-tuned LLMs.

This repository contains GGUF format quantized weights for Meta's Llama 3.2 3B Instruct model, created by bartowski. These files are optimized for use with llama.cpp, LM Studio, and other local LLM inference tools.

Meta-Llama-3.1-8B-Instruct-AWQ-INT4 is an open-source, quantized large language model optimized for instruction-following and efficient text generation. It supports API and local deployment, serving AI developers and researchers.

llama-3.3-70b-instruct-awq is a quantized version of Meta's Llama 3.3 70B Instruct model using the AWQ quantization method. This allows the large model to run with reduced memory requirements while maintaining performance. It includes a chat template optimized for instruction following and is compatible with Transformers and other inference frameworks.

This is an optimized 4-bit quantized version of the Llama 3.2 1B Instruct model created by Unsloth. It is designed for efficient local inference while maintaining strong instruction-following capabilities. The model is available on Hugging Face and works with popular LLM runtimes and fine-tuning tools.

This is a 4-bit quantized version of Meta's Llama 3.2 3B Instruct model, optimized by Unsloth for faster inference and lower memory usage. It maintains strong instruction-following capabilities while being suitable for deployment on laptops and modest GPUs. The model includes full chat templates and is compatible with the Hugging Face ecosystem.

Llama-3.1-8B-Instruct is an instruction-tuned version of Meta's Llama 3.1 8B model, optimized by Unsloth for faster training and inference. It supports chat templates, function calling, and various quantization formats for efficient local or cloud deployment. The model is intended for developers building custom AI applications, agents, or fine-tuned domain-specific assistants.

This repository hosts an AWQ-quantized version of Meta's Llama 3 70B Instruct model, created by casperhansen. It enables efficient inference of this powerful instruction-tuned model on consumer or enterprise hardware with lower VRAM requirements. The model supports chat templates and is compatible with standard Hugging Face transformers and inference tools.

This is an FP8 dynamically quantized version of Meta's Llama-3.3-70B-Instruct model. It maintains strong reasoning and instruction-following capabilities while significantly reducing memory requirements compared to the original 16-bit model. The model is suitable for local or self-hosted inference using compatible quantization and serving frameworks.

Llama-3.1-8B-Instruct is an open-source large language model developed by Meta for instruction-following and conversational AI tasks. It is designed for developers and researchers to build advanced NLP applications and is available via Hugging Face with open weights.

This is an AWQ (INT4) quantized version of Meta's Llama 3.1 70B Instruct model, optimized for reduced memory usage while maintaining performance. It includes a detailed chat template and is suitable for local inference. The model is provided by the hugging-quants organization on Hugging Face.

This is an AWQ INT4 quantized version of Meta's Llama 3.3 70B Instruct model. It enables efficient local or server-based inference while preserving most of the original model's capabilities, including tool use and reasoning. The model is hosted on Hugging Face.

Llama 3.2 3B Instruct is a web-based chatbot that uses a large language model to generate fluent, context-aware responses to user input. It supports ongoing conversations and is suitable for users seeking AI-powered chat or information assistance.

A 1B parameter version of Meta's Llama 3.2 Instruct model, quantized to 4-bit and packaged for the MLC-LLM runtime. It enables high-performance local inference across GPUs, CPUs, and mobile devices. The model is distributed via Hugging Face and supports standard chat templates for conversational use.