What are the hardware requirements for GLM 5.3 Flash W4A16 NVFP4 K32 Experts FP8 WO?

GLM 5.3 Flash W4A16 NVFP4 K32 Experts FP8 WO requires approximately 83.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed GLM 5.3 Flash W4A16 NVFP4 K32 Experts FP8 WO and how large is it?

GLM 5.3 Flash W4A16 NVFP4 K32 Experts FP8 WO is developed by ormandj, a model with 165.5b 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 Flash W4A16 NVFP4 K32 Experts FP8 WO?

GLM 5.3 Flash W4A16 NVFP4 K32 Experts FP8 WO is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GLM 5.3 Flash W4A16 NVFP4 K32 Experts FP8 WO by ormandj — VRAM 83.2GB

Name: GLM 5.3 Flash W4A16 NVFP4 K32 Experts FP8 WO
Author: ormandj

GLM 5.3 Flash W4A16 NVFP4 K32 Experts FP8 WO is an open-source language model by ormandj. Features: 165.5b LLM, VRAM: 83.2GB, License: mit, LLM Explorer Score: 0.25.

8-bit Base model:quantized:zai-org/g... Base model:zai-org/glm-5.3-fla... Conversational Endpoints compatible Fp8 Glm5 next Image-text-to-text Modelopt Modelopt mixed Nvfp4 Region:us Safetensors Sglang Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ormandj/GLM-5.3-Flash-W4A16-NVFP4-K32-Experts-FP8-WO

GLM 5.3 Flash W4A16 NVFP4 K32 Experts FP8 WO Parameters and Internals

LLM Name	GLM 5.3 Flash W4A16 NVFP4 K32 Experts FP8 WO
Repository 🤗	https://huggingface.co/ormandj/GLM-5.3-Flash-W4A16-NVFP4-K32-Experts-FP8-WO
Base Model(s)	zai-org/GLM-5.3-Flash-BF16 zai-org/GLM-5.3-Flash-BF16
Model Size	165.5b
Required VRAM	83.2 GB
Updated	2026-09-02
Maintainer	ormandj
Model Type	glm5_next
Model Files	1.3 GB: 1-of-90 1.9 GB: 2-of-90 2.0 GB: 3-of-90 2.0 GB: 4-of-90 2.0 GB: 5-of-90 2.0 GB: 6-of-90 2.0 GB: 7-of-90 2.0 GB: 8-of-90 2.0 GB: 9-of-90 2.0 GB: 10-of-90 2.0 GB: 11-of-90 2.0 GB: 12-of-90 2.0 GB: 13-of-90 2.0 GB: 14-of-90 2.0 GB: 15-of-90 2.0 GB: 16-of-90 2.0 GB: 17-of-90 2.0 GB: 18-of-90 2.0 GB: 19-of-90 2.0 GB: 20-of-90 2.0 GB: 21-of-90 2.0 GB: 22-of-90 2.0 GB: 23-of-90 2.0 GB: 24-of-90 2.0 GB: 25-of-90 2.0 GB: 26-of-90 2.0 GB: 27-of-90 2.0 GB: 28-of-90 2.0 GB: 29-of-90 2.0 GB: 30-of-90 2.0 GB: 31-of-90 2.0 GB: 32-of-90 2.0 GB: 33-of-90 2.0 GB: 34-of-90 2.0 GB: 35-of-90 2.0 GB: 36-of-90 2.0 GB: 37-of-90 2.0 GB: 38-of-90 2.0 GB: 39-of-90 2.0 GB: 40-of-90 2.0 GB: 41-of-90 2.0 GB: 42-of-90
Model Architecture	Glm5NextForConditionalGeneration
License	mit
Transformers Version	5.16.0

Rank the GLM 5.3 Flash W4A16 NVFP4 K32 Experts FP8 WO capabilities

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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 Flash W4A16 NVFP4 K32 Experts FP8 WO

Best Alternatives	Context / RAM	Downloads	Likes
GLM 5.3 Flash NVFP4 Spark	0K / 182.7 GB	8952	5
Apex Flash 1 Abliterated NVFP4	0K / 140.3 GB	43	1
GLM 5.3 Flash NVFP4	0K / 73.1 GB	0	35
GLM 5.3 Flash NVFP4	0K / 137.3 GB	51	1
GLM 5.3 Flash UNCENSORED NVFP4	0K / 69.8 GB	3210	27
...Flash UNCENSORED NVFP4 DFlash2	0K / 66.8 GB	3321	1
... Flash UNCENSORED NVFP4 DSpark	0K / 66.8 GB	1681	1

Note: green Score (e.g. "73.2") means that the model is better than ormandj/GLM-5.3-Flash-W4A16-NVFP4-K32-Experts-FP8-WO.