GLM 4.7 Flash Alternatives

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.

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.

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.

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 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.

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.

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 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.

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.

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-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.

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.

GLM-4.5-Air-FP8 is an FP8 quantized variant of the GLM-4.5 model, designed for efficient local inference. It supports tool calling and includes a comprehensive chat template. The model is suitable for developers building local AI applications and is distributed via Hugging Face for use with standard inference frameworks.

GLM-4.6V-Flash-MLX-6bit is a quantized multimodal model hosted on Hugging Face by the lmstudio-community. It belongs to the class of foundation models and is distributed as an MLX-optimized 6-bit version intended for local inference on compatible hardware. The model includes a chat template that supports tool calling. When tools are provided, the template instructs the model to output function calls in a specific XML format enclosed in tool_call tags, with individual arguments expressed through arg_key and arg_value elements. The template also defines handling for multimodal content that mixes text and images, using special tokens such as begin_of_image and image. It is delivered as a repository on the Hugging Face platform, allowing download of the model files for use with the MLX framework. The page references a pad_token set to the end-of-text token and supplies the full chat template as part of the configuration. No pricing, licensing terms, or explicit target audience beyond the general Hugging Face modeling community are stated.

An NVIDIA-optimized version of the GLM-5 large language model using NVFP4 precision for accelerated inference on compatible GPUs. It includes support for tool calling and follows standard chat templates, making it suitable for deployment in performance-sensitive local or on-premise environments.

GLM-4.7-AWQ is a quantized variant of the GLM-4.7 open-source large language model, optimized using AWQ for reduced memory usage and faster inference on GPUs. It supports advanced features such as function/tool calling via a specialized chat template and can be used for text generation, coding assistance, and structured output tasks. The model is hosted on Hugging Face and is intended for developers who want to self-host or run capable LLMs locally or in their own infrastructure.

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.

A GGUF quantized version of the GLM-5.2 model provided by Unsloth. It supports advanced features such as tool calling and high-reasoning modes. The model is designed for efficient local deployment using inference engines that support the GGUF format, making powerful language models accessible on standard hardware.

GLM-4.5-Air is an efficient variant of the GLM-4.5 series of large language models. It supports tool calling and follows a chat template suitable for instruction and agentic use cases. The model is hosted on Hugging Face and intended for inference with the Transformers library or compatible frameworks.

GLM-5.2-FP8 is an open-source large language model optimized for local inference with FP8 precision. It allows developers to run advanced text generation tasks efficiently on their own hardware.

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.

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 an optimized version of the GLM-4.5-Air model prepared for use with the Unsloth library. It includes a specialized chat template and tokenizer configuration for tool calling and multi-turn conversations. The model is designed to be used with Unsloth's efficient training and inference methods for large language models.