Qwythos-9B-v2-MLX-8bit is a quantized checkpoint of a 9B parameter language model, distributed for efficient local inference and text generation. Below are 14 foundation models & chat apps with similar functionality to Qwythos 9B, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
Qwythos-9B-v2-MLX-6bit is a 9B parameter language model distributed in MLX 6-bit quantized format. It is designed for developers seeking efficient, local LLM inference with reduced memory requirements.
Qwythos-9B-v2-MXFP8 is an open-source large language model supporting both text and vision tasks. It is designed for developers and researchers seeking a customizable, fine-tuned model for advanced AI applications. The model is available via pip and npm for easy integration.
Qwythos-9B-v2-MXFP4 is an open-source large language model designed for natural language processing and text generation. It can be run locally or integrated into custom ML pipelines, making it suitable for developers and researchers who require customizable LLMs. The model is distributed via Hugging Face with open weights and supports instruction following.
Qwythos-9B-v2-AutoRound-W4A16-RTN is an open-source, quantized large language model designed for local inference and conversational AI. It is suitable for developers and researchers seeking efficient, offline AI capabilities.
Qwen3.5-27B-MLX-4.5bit is an open-source, quantized large language model designed for efficient local text generation using the MLX framework. It supports local inference and is suitable for developers and researchers seeking to run LLMs on their own hardware.
Qwen3.5-9B-quantized.w4a16 is a quantized version of the Qwen3.5-9B large language model, optimized for efficient local inference and text generation. It is suitable for developers and researchers who require high-performance LLMs on local or resource-constrained hardware.
Qwen3.6-35B-A3B-CompQuant-MLX-3bit is an open-source, quantized large language model optimized for local inference. It features 3-bit compression and MLX compatibility, making it suitable for researchers and developers needing efficient LLMs.
Qwen3.6-35B-A3B-MLX-3bit is an open-source, quantized checkpoint of the Qwen3.6-35B language model, compatible with MLX for efficient local inference. It enables AI researchers and developers to run advanced text generation models on their own infrastructure, supporting experimentation, fine-tuning, and deployment in custom applications.
Qwen3.5-9B-IQ4_NL-GGUF is an open-source checkpoint of the Qwen 3.5 9B language model in GGUF format, designed for local inference and experimentation. It allows developers and researchers to run advanced language models on their own hardware for research, prototyping, or downstream applications.
qwen2.5-7b-numbers-albanese-s1 is an open-source large language model hosted on Hugging Face, designed for advanced text generation tasks. It supports both API and local inference, making it suitable for research, experimentation, and integration into AI applications. The model is accessible to developers and researchers seeking customizable, non-proprietary AI solutions.
qwen2.5-7b-numbers-albanese-s5 is an open-source fine-tuned Qwen2.5 7B language model for text generation and chat applications. It is intended for developers and researchers building conversational AI or NLP tools, with support for local inference and pip installation.
qwen2.5-7b-numbers-albanese-s2 is an open-source large language model checkpoint available on Hugging Face. It supports text generation, fine-tuning, and experimentation for AI research and NLP applications, enabling local or cloud-based inference.
Qwen3.6-35B-A3B-MLX-VQ-2.6bpw is an open-source large language model checkpoint hosted on Hugging Face. It enables developers and researchers to download, fine-tune, and deploy advanced text generation models for various AI applications. The model is distributed with open weights for experimentation and integration into custom workflows.
qwen2.5-7b-numbers-albanese-s4 is a variant of the Qwen2.5-7B language model, fine-tuned for enhanced instruction following and conversational tasks. It is distributed as open source for local inference and research applications.
