What are the hardware requirements for GLM 5.2 4bit?

GLM 5.2 4bit requires approximately 207.5 GB of VRAM and supports a context window of 1024K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed GLM 5.2 4bit and how large is it?

GLM 5.2 4bit is developed by mlx-community, a model with 743.4b 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 5.2 4bit?

GLM 5.2 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GLM 5.2 4bit by mlx-community — VRAM 207.5GB, 1024K context

Name: GLM 5.2 4bit
Author: mlx-community

GLM 5.2 4bit is an open-source language model by mlx-community. Features: 743.4b LLM, VRAM: 207.5GB, Context: 1024K, License: mit, MoE, Quantized, LLM Explorer Score: 0.31.

4-bit 4bit Base model:quantized:zai-org/g... Base model:zai-org/glm-5.2 Conversational Glm moe dsa Mlx Moe Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/GLM-5.2-4bit

GLM 5.2 4bit Parameters and Internals

LLM Name	GLM 5.2 4bit
Repository 🤗	https://huggingface.co/mlx-community/GLM-5.2-4bit
Base Model(s)	zai-org/GLM-5.2 zai-org/GLM-5.2
Model Size	743.4b
Required VRAM	207.5 GB
Updated	2026-07-30
Maintainer	mlx-community
Model Type	glm_moe_dsa
Model Files	4.9 GB: 1-of-91 5.3 GB: 2-of-91 3.9 GB: 3-of-91 5.4 GB: 4-of-91 3.9 GB: 5-of-91 5.3 GB: 6-of-91 3.8 GB: 7-of-91 5.3 GB: 8-of-91 4.0 GB: 9-of-91 5.3 GB: 10-of-91 3.9 GB: 11-of-91 5.3 GB: 12-of-91 3.8 GB: 13-of-91 5.4 GB: 14-of-91 3.9 GB: 15-of-91 5.3 GB: 16-of-91 3.9 GB: 17-of-91 5.3 GB: 18-of-91 3.9 GB: 19-of-91 5.3 GB: 20-of-91 3.9 GB: 21-of-91 5.3 GB: 22-of-91 4.0 GB: 23-of-91 5.3 GB: 24-of-91 3.8 GB: 25-of-91 5.3 GB: 26-of-91 3.9 GB: 27-of-91 5.4 GB: 28-of-91 3.9 GB: 29-of-91 5.3 GB: 30-of-91 3.8 GB: 31-of-91 5.3 GB: 32-of-91 4.0 GB: 33-of-91 5.3 GB: 34-of-91 3.9 GB: 35-of-91 5.3 GB: 36-of-91 3.8 GB: 37-of-91 5.4 GB: 38-of-91 3.9 GB: 39-of-91 5.3 GB: 40-of-91 3.9 GB: 41-of-91 5.3 GB: 42-of-91 3.9 GB: 43-of-91 5.3 GB: 44-of-91 3.9 GB: 45-of-91
Quantization Type	4bit
Model Architecture	GlmMoeDsaForCausalLM
License	mit
Context Length	1048576
Model Max Length	1048576
Transformers Version	5.12.0
Vocabulary Size	154880

Rank the GLM 5.2 4bit 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 5.2 4bit

Best Alternatives	Context / RAM	Downloads	Likes
GLM 5.2 DQ4plus Q8	1024K / 184.6 GB	9208	16
GLM 5.2 Mxfp4	1024K / 233.5 GB	18445	22
GLM 5.2 MLX Nvfp4	1024K / 207.5 GB	4741	3
Aesop V1	1024K / 210.9 GB	905	4

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/GLM-5.2-4bit.