What are the hardware requirements for GLM 5.3 CYBERSECURITY FP8?

GLM 5.3 CYBERSECURITY FP8 requires approximately 112.6 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 CYBERSECURITY FP8 and how large is it?

GLM 5.3 CYBERSECURITY FP8 is developed by dealignai, a model with 753.3b 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 CYBERSECURITY FP8?

GLM 5.3 CYBERSECURITY FP8 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GLM 5.3 CYBERSECURITY FP8 by dealignai — VRAM 112.6GB, 1024K context

Name: GLM 5.3 CYBERSECURITY FP8
Author: dealignai

GLM 5.3 CYBERSECURITY FP8 is an open-source language model by dealignai. Features: 753.3b LLM, VRAM: 112.6GB, Context: 1024K, License: mit, MoE, LLM Explorer Score: 0.39.

Abliterated Ar Base model:jangq-ai/glm-5.3-fp... Base model:quantized:jangq-ai/... Conversational Crack Cybersecurity Domain-specific En Es Fp8 Fr Glm Glm moe dsa Hi Ja Ko Moe Offensive-security Pentest Red-team Refusal-removed Region:us Ru Safetensors Sharded Sr Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/dealignai/GLM-5.3-CYBERSECURITY-FP8

GLM 5.3 CYBERSECURITY FP8 Parameters and Internals

LLM Name	GLM 5.3 CYBERSECURITY FP8
Repository 🤗	https://huggingface.co/dealignai/GLM-5.3-CYBERSECURITY-FP8
Base Model(s)	zai-org/GLM-5.3 JANGQ-AI/GLM-5.3-FP8 zai-org/GLM-5.3 JANGQ-AI/GLM-5.3-FP8
Model Size	753.3b
Required VRAM	112.6 GB
Updated	2026-09-01
Maintainer	dealignai
Model Type	glm_moe_dsa
Model Files	4.6 GB: 1-of-282 2.7 GB: 2-of-282 2.7 GB: 3-of-282 2.7 GB: 4-of-282 2.7 GB: 5-of-282 2.7 GB: 6-of-282 2.7 GB: 7-of-282 2.7 GB: 8-of-282 2.7 GB: 9-of-282 2.7 GB: 10-of-282 2.7 GB: 11-of-282 2.7 GB: 12-of-282 2.7 GB: 13-of-282 2.7 GB: 14-of-282 2.7 GB: 15-of-282 2.7 GB: 16-of-282 2.7 GB: 17-of-282 2.7 GB: 18-of-282 2.7 GB: 19-of-282 2.7 GB: 20-of-282 2.7 GB: 21-of-282 2.7 GB: 22-of-282 2.7 GB: 23-of-282 2.7 GB: 24-of-282 2.7 GB: 25-of-282 2.7 GB: 26-of-282 2.7 GB: 27-of-282 2.7 GB: 28-of-282 2.7 GB: 29-of-282 2.7 GB: 30-of-282 2.7 GB: 31-of-282 2.7 GB: 32-of-282 2.7 GB: 33-of-282 2.7 GB: 34-of-282 2.7 GB: 35-of-282 2.7 GB: 36-of-282 2.7 GB: 37-of-282 2.7 GB: 38-of-282 2.7 GB: 39-of-282 2.7 GB: 40-of-282 2.7 GB: 41-of-282
Supported Languages	en zh ru sr hi fr es ar ko ja
Model Architecture	GlmMoeDsaForCausalLM
License	mit
Context Length	1048576
Model Max Length	1048576
Transformers Version	5.15.0
Vocabulary Size	154880

Rank the GLM 5.3 CYBERSECURITY FP8 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 CYBERSECURITY FP8

Best Alternatives	Context / RAM	Downloads	Likes
GLM 5.3	1024K / 232.2 GB	8804	1255
GLM 5.2	1024K / 232 GB	2391730	4875
GLM 5.3 BF16	1024K / 237.4 GB	482	24
GLM 5.3	1024K / 237.4 GB	379	6
GLM 5.3 W4A16	1024K / 73.9 GB	268	1
GLM 5.3	1024K / 232.2 GB	118	1
GLM 5.2 MXFP4xMXFP8	1024K / 68.1 GB	296	2
GLM 5.2	1024K / 237.4 GB	1671	26
MISS V0	1024K / 232 GB	205	1
GLM 5.2	1024K / 232 GB	116	1

Note: green Score (e.g. "73.2") means that the model is better than dealignai/GLM-5.3-CYBERSECURITY-FP8.