Llama 3.1 8B Instruct Alternatives

This is a Red Hat optimized FP8 quantized variant of Meta's Llama 3.1 8B Instruct model. It supports chat, tool calling, and code interpretation while using less memory. Targeted at enterprise and open-source developers seeking performant, locally runnable LLMs.

This is a quantized version of Meta's Llama 3.1 8B Instruct model using FP8 precision for the KV cache, optimized for AMD hardware. It is hosted on Hugging Face and can be used with the Transformers library for text generation and chat applications. The model is intended for developers seeking efficient local inference with reduced memory requirements.

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 repository contains the FP8 quantized version of Meta's Llama-4-Maverick-17B-128E-Instruct model. It is an open-weights large language model optimized for instruction following, tool calling, and long-context tasks. The model can be used with the Hugging Face Transformers library, local inference engines, or cloud providers.

This is an FP8-quantized version of Meta's Llama 3.1 70B Instruct model, published by RedHatAI. It maintains strong instruction-following capabilities while using a more memory-efficient format suitable for self-hosted deployment. The model includes a detailed chat template and is designed for production inference environments.

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 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 is an FP8 quantized checkpoint of NVIDIA's Llama-4 Scout 17B model with 16 experts. It is released under the NVIDIA Open Model License and supports commercial use and derivative works. The model is designed for instruction following and general language tasks.

RedHatAI/Llama-3.2-1B-Instruct-FP8-dynamic is a quantized, instruction-tuned large language model based on the Llama architecture. It is open source, supports text generation and fine-tuning, and is suitable for AI researchers and developers seeking efficient, customizable LLMs for experimentation or integration.

An FP8 dynamically quantized version of Meta's Llama 3.1 8B Instruct model created by RedHatAI. It maintains high performance while significantly reducing memory footprint for local or self-hosted inference. The model supports standard chat templates and is optimized for efficient deployment.

Meta-Llama-3-8B-Instruct is an 8 billion parameter language model hosted on Hugging Face under the NousResearch organization. It belongs to the Llama 3 family and serves as an instruction-tuned variant intended for conversational and assistant-style applications. The model uses the LlamaForCausalLM architecture with a model type of llama. Its tokenizer configuration includes a specific chat template that structures messages with role-based headers, beginning-of-text and end-of-text tokens, and support for an add-generation-prompt flag to prepare responses from an assistant role. The configuration also defines bos_token as <|begin_of_text| and eos_token as <|eot_id|. It is delivered as a repository on the Hugging Face platform, where it can be accessed for download and use in machine learning workflows. The page indicates substantial community engagement through over two million all-time downloads. The model was created on April 18, 2024. As a foundation model, it is positioned for research, fine-tuning, and integration into local AI systems that require instruction following. The repository is part of the broader Hugging Face ecosystem for open-source machine learning models.

This is the 8B Instruct version of Meta's Llama 3.1 model, hosted by Unsloth on Hugging Face. It supports instruction following, tool use, and long context windows. The model is widely used for local inference, fine-tuning, and as a base for custom applications via the Transformers library.

This is an NVIDIA-maintained quantized version of a Llama 3.3-based Nemotron Super model with 49B parameters in FP8 format. It includes a custom chat template and is designed for efficient text generation and conversational AI. The model is hosted on Hugging Face and can be used with the Transformers library.

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 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.

This is a FP8 quantized version of Meta's Llama 3.1 8B model, published by RedHatAI. It supports multiple languages including English, German, French, and Italian. The model is compatible with the transformers library and vLLM, making it suitable for efficient text generation in production environments.

This is a community-hosted version of Meta's Llama 3.1 8B Instruct model. It has been optimized for dialogue, tool calling, and following complex instructions. With a 128k context window, it is suitable for a wide range of applications including coding assistance, agentic workflows, and general chat. The model is fully open and available in multiple formats on Hugging Face.

Llama 3.2 1B Instruct Q8 0 is a quantized GGUF version of the Llama 3.2 1B Instruct model hosted on Hugging Face by the Hugging Quants organization. It belongs to the class of foundation models and supports text generation and conversational tasks across eight languages. The model card indicates it uses the Llama architecture from Meta and includes a specific chat template with tokens such as bos_token, eos_token, and structured role-based formatting for assistant responses. The repository provides the file llama-3.2-1b-instruct-q8_0.gguf along with associated metadata confirming it is quantized. Total file size is listed as 1,321,079,200 bytes. It carries tags for GGUF, PyTorch, llama.cpp, and facebook/meta/llama families, positioning it for use in compatible inference runtimes that handle this format. Hugging Quants maintains the repository, which has accumulated around 50 likes and hosts four discussions. The page forms part of the broader Hugging Face ecosystem for models, datasets, and related resources focused on open-source AI.

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.

This is a bitsandbytes 4-bit quantized version of Meta's Llama 3.1 8B Instruct model, optimized by Unsloth for faster training and inference. It includes a custom chat template supporting tools and is designed for efficient local deployment using popular inference libraries.

Llama 3.1 8B is a text-generation model hosted on Hugging Face under the identifier meta-llama/Llama-3.1-8B. It belongs to the class of foundation models and carries the pipeline tag text-generation. The model is made available through the Hugging Face platform where it can be accessed for download and inference. It uses the transformers library and includes a tokenizer configuration with defined beginning-of-text and end-of-text tokens. Inference providers such as featherless-ai list it with live status for the text-generation task. Uploaded in July 2024 and last modified in October 2024, the model has recorded more than 26 million all-time downloads and maintains an active community presence with over two thousand likes. It appears in collections and supports integration within the broader Hugging Face ecosystem of models, datasets, and spaces. No specific licensing, pricing, or target user roles are stated on the page. The surrounding Hugging Face site promotes open source and open science as part of its mission.

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.

Llama-3.2-1B-Instruct is an open-source, instruction-tuned language model from Meta, designed for text generation and conversational AI. It is suitable for developers and researchers building chatbots, virtual assistants, and other NLP applications.