What are the hardware requirements for GLM 4.7 Flash 8bit Gs32?

GLM 4.7 Flash 8bit Gs32 requires approximately 33.6 GB of VRAM and supports a context window of 198K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed GLM 4.7 Flash 8bit Gs32 and how large is it?

GLM 4.7 Flash 8bit Gs32 is developed by mlx-community, a model with 29.9b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate GLM 4.7 Flash 8bit Gs32?

GLM 4.7 Flash 8bit Gs32 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GLM 4.7 Flash 8bit Gs32 by mlx-community — VRAM 33.6GB, 198K context

Name: GLM 4.7 Flash 8bit Gs32
Author: mlx-community

GLM 4.7 Flash 8bit Gs32 is an open-source language model by mlx-community. Features: 29.9b LLM, VRAM: 33.6GB, Context: 198K, License: mit, MoE, Quantized, LLM Explorer Score: 0.22.

8-bit 8bit Base model:quantized:zai-org/g... Base model:zai-org/glm-4.7-fla... Conversational En Glm4 moe lite Mlx Moe Quantized Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/mlx-community/GLM-4.7-Flash-8bit-gs32

GLM 4.7 Flash 8bit Gs32 Parameters and Internals

LLM Name	GLM 4.7 Flash 8bit Gs32
Repository 🤗	https://huggingface.co/mlx-community/GLM-4.7-Flash-8bit-gs32
Base Model(s)	zai-org/GLM-4.7-Flash zai-org/GLM-4.7-Flash
Model Size	29.9b
Required VRAM	33.6 GB
Updated	2026-07-13
Maintainer	mlx-community
Model Type	glm4_moe_lite
Model Files	5.2 GB: 1-of-7 5.3 GB: 2-of-7 5.2 GB: 3-of-7 5.2 GB: 4-of-7 5.3 GB: 5-of-7 5.2 GB: 6-of-7 2.2 GB: 7-of-7
Supported Languages	en zh
Quantization Type	8bit
Model Architecture	Glm4MoeLiteForCausalLM
License	mit
Context Length	202752
Model Max Length	202752
Transformers Version	5.0.0rc0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Vocabulary Size	154880

Rank the GLM 4.7 Flash 8bit Gs32 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to GLM 4.7 Flash 8bit Gs32

Best Alternatives	Context / RAM	Downloads	Likes
GLM 4.7 Flash 8bit	198K / 31.9 GB	3470	24
GLM 4.7 Flash 8bit Mxfp8	198K / 30.7 GB	693	1
GLM 4.7 Flash 4bit	198K / 17 GB	7029	66
GLM 4.7 Flash 6bit	198K / 24.2 GB	4053	7
....5 High Reasoning Distill 4bit	198K / 17 GB	390	4
GLM 4.7 Flash 4bit Mxfp4	198K / 15.9 GB	237	4
....5 High Reasoning Distill 6bit	198K / 24.2 GB	197	2
....5 High Reasoning Distill 8bit	198K / 31.9 GB	178	1
GLM 4.7 Flash Abliteratex	198K / 62.3 GB	510	3
Glm 4.7 Flash Opus Reasoning	198K / 59.9 GB	10	0

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/GLM-4.7-Flash-8bit-gs32.