What are the hardware requirements for GLM 5.3 Mixed 4 5bit?

GLM 5.3 Mixed 4 5bit requires approximately 181.5 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 5.3 Mixed 4 5bit and how large is it?

GLM 5.3 Mixed 4 5bit 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 5.3 Mixed 4 5bit?

GLM 5.3 Mixed 4 5bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GLM 5.3 Mixed 4 5bit by mlx-community — VRAM 181.5GB, 1024K context

Name: GLM 5.3 Mixed 4 5bit
Author: mlx-community

GLM 5.3 Mixed 4 5bit is an open-source language model by mlx-community. Features: 743.4b LLM, VRAM: 181.5GB, Context: 1024K, License: other, MoE, Quantized, LLM Explorer Score: 0.32.

4-bit 5bit Base model:quantized:zai-org/g... Base model:zai-org/glm-5.3-bf1... Conversational En Glm moe dsa Mlx Moe Quantized Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/mlx-community/GLM-5.3-mixed-4_5bit

GLM 5.3 Mixed 4 5bit Parameters and Internals

LLM Name	GLM 5.3 Mixed 4 5bit
Repository 🤗	https://huggingface.co/mlx-community/GLM-5.3-mixed-4_5bit
Base Model(s)	zai-org/GLM-5.3-BF16 zai-org/GLM-5.3-BF16
Model Size	743.4b
Required VRAM	181.5 GB
Updated	2026-09-06
Maintainer	mlx-community
Model Type	glm_moe_dsa
Model Files	5.1 GB: 1-of-113 4.2 GB: 2-of-113 4.2 GB: 3-of-113 3.6 GB: 4-of-113 4.2 GB: 5-of-113 4.2 GB: 6-of-113 3.6 GB: 7-of-113 4.2 GB: 8-of-113 4.2 GB: 9-of-113 3.6 GB: 10-of-113 4.2 GB: 11-of-113 4.2 GB: 12-of-113 3.6 GB: 13-of-113 4.2 GB: 14-of-113 4.2 GB: 15-of-113 3.6 GB: 16-of-113 4.2 GB: 17-of-113 4.2 GB: 18-of-113 3.6 GB: 19-of-113 4.2 GB: 20-of-113 4.2 GB: 21-of-113 3.6 GB: 22-of-113 4.2 GB: 23-of-113 4.2 GB: 24-of-113 3.6 GB: 25-of-113 4.2 GB: 26-of-113 4.2 GB: 27-of-113 3.6 GB: 28-of-113 4.2 GB: 29-of-113 4.2 GB: 30-of-113 3.6 GB: 31-of-113 4.2 GB: 32-of-113 4.2 GB: 33-of-113 3.6 GB: 34-of-113 4.2 GB: 35-of-113 4.2 GB: 36-of-113 3.6 GB: 37-of-113 4.2 GB: 38-of-113 4.2 GB: 39-of-113 3.6 GB: 40-of-113 4.2 GB: 41-of-113 4.2 GB: 42-of-113 3.6 GB: 43-of-113 4.2 GB: 44-of-113 4.2 GB: 45-of-113
Supported Languages	en zh
Quantization Type	5bit
Model Architecture	GlmMoeDsaForCausalLM
License	other
Context Length	1048576
Model Max Length	1048576
Transformers Version	5.15.0
Vocabulary Size	154880

Rank the GLM 5.3 Mixed 4 5bit 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 5.3 Mixed 4 5bit

Best Alternatives	Context / RAM	Downloads	Likes
GLM 5.2 DQ4plus Q8	1024K / 184.6 GB	9208	16
GLM 5.2 4bit	1024K / 207.5 GB	9403	5
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-5.3-mixed-4_5bit.