GLM 4.6V Flash Alternatives

GLM-4.6V-Flash-MLX-4bit is a 4-bit quantized version of the GLM-4.6V-Flash multimodal model hosted on Hugging Face by the lmstudio-community. It is distributed as part of the collection of models available for local AI runtimes. The model includes a chat template that supports tools through XML-formatted function calls. It handles multimodal inputs by processing both text strings and image content marked with specific tokens such as <|begin_of_image| and <|image|. The configuration specifies a pad token of <|endoftext|. It is delivered as a repository on the Hugging Face platform, where models can be downloaded for integration into compatible local inference frameworks. The page appears under the lmstudio-community organization, indicating suitability for users running models through LM Studio or similar environments. No pricing or licensing details are stated on the model page. The surrounding Hugging Face site promotes open source and open science but does not attribute a specific license to this quantized variant.

This is an 8-bit quantized version of the GLM-4.6V-Flash model using MLX, designed for efficient local execution. It supports multimodal inputs including text and images and includes tooling capabilities. The model is distributed via Hugging Face for use with local inference tools like LM Studio.

GLM-4.6V-Flash is an open-weights multimodal foundation model from zai-org that processes both text and images. It supports advanced features such as tool calling and is distributed on Hugging Face for local or self-hosted inference. The model is intended for developers building vision-language applications or integrating multimodal capabilities into their own systems.

This is a 6-bit quantized version of the GLM-4.7-Flash model, prepared by the LM Studio community for efficient inference using the MLX framework on Apple devices. It includes support for tool calling and follows a standard chat template. The model is hosted on Hugging Face for easy local deployment.

GLM-4.7-Flash-MLX-8bit is a community-quantized version of the GLM-4 large language model using 8-bit precision and optimized for the MLX framework on Apple silicon. It supports tool calling and can be used locally through libraries such as Transformers or MLX. The model is hosted on Hugging Face for easy download and integration into local AI applications.

GLM-4.7-Flash is an optimized, high-speed variant of Zhipu AI's GLM-4 model, prepared by Unsloth for efficient deployment. It supports tool calling, structured output, and standard chat templates. The model is aimed at developers who require fast, cost-effective language model inference for production applications.

GLM-4.7-Flash is a foundation model hosted on Hugging Face under the repository zai-org/GLM-4.7-Flash. It belongs to the class of large language models that process text through a defined chat template. The model includes a chat template in Jinja format that supports tool use. When tools are supplied, the template instructs the model to consider function signatures provided inside XML-style tags and to output calls in a specific XML format containing the function name along with argument keys and values. A visible_text macro within the template handles string content, iterable collections, and mapping objects by extracting text where present. The tokenizer configuration specifies an end-of-text token as the pad token. The model is delivered as a repository on the Hugging Face platform, where users can access the associated configuration files. Hugging Face itself operates to advance and democratize artificial intelligence through open source and open science. No pricing, licensing terms, or specific target audience beyond the general context of model repositories are stated.

This repository provides GGUF quantized weights of the GLM-4.7-Flash model, optimized for use with LM Studio, llama.cpp, and other GGUF-compatible engines. It includes support for tool calling and is intended for local CPU/GPU inference of the GLM series of large language models.

GLM-4.7-Flash-NVFP4 is a quantized variant of the GLM-4.7 language model hosted on Hugging Face. It is provided by user GadflyII under the repository name GLM-4.7-Flash-NVFP4 and uses NVFP4 precision for reduced memory and compute requirements during inference. The model includes a chat template that supports tool calling. When tools are supplied, the template instructs the model to output function calls in a specific XML format enclosed in tool_call tags, with individual arguments expressed as arg_key and arg_value pairs. A visible_text macro handles content rendering for strings, iterables, or mappings containing text items. The tokenizer configuration specifies an end-of-text token as the pad token. It is distributed as a model repository on the Hugging Face platform. Users obtain the files through the standard Hugging Face ecosystem for loading with compatible inference libraries. The page provides no information on licensing, pricing, or intended audience beyond the general Hugging Face context of open-source and open-science AI advancement.

GLM-4.5V is a vision-enabled version of the GLM-4.5 large language model. It supports image inputs, tool calling via structured XML formats, and custom chat templates. The model weights are hosted on Hugging Face for developers to integrate into applications or run locally.

This is a quantized (6-bit) version of the LFM2-24B model in MLX format, suitable for efficient inference on Apple devices. It includes a chat template and is distributed via Hugging Face for use with MLX and related tools.

unsloth/GLM-4.7-Flash-GGUF contains GGUF quantized files for the GLM-4.7 Flash model. It includes support for tool calling using XML-style function call formatting. The model is suitable for local deployment using llama.cpp or other GGUF-compatible runtimes and is provided to enable efficient on-premise or desktop AI applications.

This repository hosts an AWQ 4-bit quantized version of the GLM-4.7-Flash model, optimized for reduced memory usage and faster inference. It retains tool-calling capabilities and a full chat template, making it suitable for local or hosted deployment where full-precision models would be too large. The model is provided for developers seeking efficient open-weight alternatives.

This is a quantized (5-bit) version of the LFM2-24B model in MLX format, suitable for efficient inference on Apple devices. It includes a chat template and is distributed via Hugging Face for use with MLX and related tools.

An AMD-published quantized version of the GLM-5.2 large language model using MXFP4 precision. The repository includes chat templates supporting tool use, reasoning effort levels, and system prompts. It is designed for compatibility with Hugging Face pipelines and AMD inference runtimes.

This is a 4-bit quantized version of the LFM2-24B model using the MLX framework, optimized for Apple silicon devices. Hosted by the LM Studio community, it enables efficient local inference of a large language model on Macs. The model includes a comprehensive chat template supporting tools and system prompts.

GLM-5.2 is an open-source large language model designed for advanced text generation and natural language processing tasks. It is suitable for developers and researchers seeking customizable, local deployment of LLMs with open weights.

unsloth/GLM-4.7-Flash-FP8-Dynamic is an FP8 dynamically quantized version of the GLM-4.7-Flash model. Created by Unsloth, it enables efficient local inference with significantly reduced VRAM requirements while maintaining model quality. The model includes a custom chat template and is compatible with the Transformers library and other inference engines.

A 4-bit quantized version of the LFM2.5 1.2B Instruct model optimized for the MLX framework on Apple Silicon. It is designed for local inference on Macs and includes a chat template suitable for instruction following. The model is distributed via Hugging Face for use with MLX and LM Studio.

This repository hosts an 8-bit quantized MLX version of the LFM2-24B model optimized for Apple Silicon. It includes a custom chat template with system prompt and tool support. The model is designed for local inference on Macs using the MLX framework and is distributed via Hugging Face.

GLM-4.5 is an open-source large language model supporting vision inputs, tool calling, and advanced chat templates. It can process images and text together and follows structured function-calling formats. The model is distributed on Hugging Face and supports Docker and pip-based inference.

This is a community-converted 4-bit quantized version of Gemma-4-E2B-it optimized for the MLX framework on Apple devices. It provides an instruction-tuned large language model that can run locally with reduced memory requirements. The model is intended for developers using the MLX ecosystem.

This is a 6-bit quantized GGUF variant of the Gemma 4 E2B instruction-tuned model, optimized for the MLX framework on Apple hardware. It allows efficient local inference of a capable language model on Macs and other Apple Silicon devices. The model includes a chat template and is suitable for local AI application development.

LFM2.5-1.2B-Instruct-MLX-8bit is a small instruction-tuned language model provided in an 8-bit quantized format optimized for the MLX framework on Apple devices. It supports tool use and system prompts. The model is hosted on Hugging Face for easy integration into local AI applications and experimentation.

LFM2.5-1.2B-Instruct-MLX-6bit is a 6-bit quantized version of a 1.2 billion parameter instruction-tuned language model optimized for the MLX framework on Apple silicon. It includes a chat template and supports tool use. The model is distributed on Hugging Face for local inference on Macs and is suitable for developers seeking lightweight on-device AI capabilities.

This is a 5-bit quantized version of Google's Gemma-4 26B model (A4B instruction-tuned variant) optimized for the MLX framework. It is hosted on Hugging Face and designed for local inference on Apple Silicon hardware, allowing developers to run a capable language model with significantly reduced memory footprint compared to the original.

This is a community-quantized 8-bit MLX version of Google's Gemma 4 26B instruction-tuned model. It is optimized for local inference on Apple devices using the MLX framework and is available for download from Hugging Face.

This is a 4-bit quantized version of Google's Gemma 4 26B instruction-tuned (it) model, optimized for the MLX framework on Apple hardware. It is designed for local inference with reduced memory footprint while maintaining performance. The model is hosted on Hugging Face and is part of the LM Studio community collection.

This repository contains an NVFP4 quantized variant of GLM-5.2 for optimized inference on NVIDIA hardware. It includes support for tool calling and advanced reasoning modes. The model follows a specific system prompt format and can be used with compatible inference engines.