Meta Llama 3 8B Instruct Alternatives

Meta-Llama-3.1-8B-Instruct-GGUF provides GGUF quantized files for Meta's Llama 3.1 8B Instruct model. It supports multiple quantization levels (Q2_K through Q8_0) for efficient local execution. The model is used by developers who want to run a capable instruction-tuned LLM on consumer-grade hardware without relying on cloud APIs.

This is a community-quantized GGUF version of Meta's Llama 3.1 8B Instruct model, optimized for use with LM Studio and other local inference tools. It provides an instruction-tuned 8 billion parameter language model that can run efficiently on consumer CPUs and GPUs. The GGUF format enables flexible quantization levels to balance performance and resource requirements for local AI applications.

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.

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.

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 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 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.

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 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 repository contains an INT4 (w4a16) quantized version of Meta's Llama-3.1-8B-Instruct model. It enables efficient inference on hardware with limited resources while preserving most of the original model's instruction-following capabilities. The model is distributed for use with Transformers and compatible inference engines.

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.

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 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.

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.

A quantized (w4a16) version of Meta's Llama 3.1 70B Instruct model provided by RedHatAI. It maintains the strong instruction-following and reasoning capabilities of the original while using 4-bit weights for more efficient inference. The model is compatible with standard Hugging Face and vLLM inference stacks.

Meta Llama 3 8B Instruct is an 8 billion parameter instruction-tuned language model published on Hugging Face. It is designed for conversational applications and text generation, providing a defined chat template that structures messages with special tokens such as start and end headers along with end-of-turn markers. The model includes an explicit chat template in its configuration that processes conversation turns by prefixing each with role identifiers, applies trimming, prepends a beginning-of-sequence token to the first message, and appends an assistant prompt when generation is required. It defines an end-of-sequence token as the end-of-turn identifier. These elements support consistent formatting for dialogue-based inference. The model is hosted as a public repository on the Hugging Face platform under the meta-llama organization. It records over 44 million all-time downloads and nearly 1.5 million recent downloads. Inference providers are listed for conversational tasks, though one shows an error status. The page was created on April 17, 2024. Hugging Face itself operates with the stated goal of advancing and democratizing artificial intelligence through open source and open science. No pricing, licensing terms, or additional capabilities are detailed in the repository metadata.

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-3-70B-Instruct is the instruction-tuned version of Meta's 70 billion parameter Llama 3 model. It excels at dialogue, reasoning, and following complex instructions. The model weights are publicly available on Hugging Face and can be used with the Transformers library or optimized inference runtimes. It is intended for developers and researchers building advanced AI applications.

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 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.

NousResearch/Meta-Llama-3-8B is a popular hosted copy of Meta's Llama 3 8B model on Hugging Face. It is a decoder-only transformer pretrained on a massive corpus and is suitable for text generation and fine-tuning. The model can be run locally with Transformers or through various inference providers.

Llama 3.1 405B Instruct is Meta's flagship open-weights large language model. It supports advanced chat templates, tool calling, and high-quality instruction following. The model is available on Hugging Face for download and can be used with various inference frameworks and providers.

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 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 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 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 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.

Llama-3.1-8B-Instruct-FP8 is an FP8 quantized version of Meta's Llama 3.1 8B instruct model, optimized by NVIDIA for high-performance inference. It maintains strong instruction-following capabilities while benefiting from reduced memory bandwidth and faster execution on compatible NVIDIA GPUs. The model is hosted on Hugging Face and is intended for developers building efficient LLM-powered applications.

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.

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.