What are the hardware requirements for Cyberneurova GLM 5.3 Flash BF16?

Cyberneurova GLM 5.3 Flash BF16 requires approximately 471.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Cyberneurova GLM 5.3 Flash BF16 and how large is it?

Cyberneurova GLM 5.3 Flash BF16 is developed by cyberneurova, a model with 321.3b 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 Cyberneurova GLM 5.3 Flash BF16?

Cyberneurova GLM 5.3 Flash BF16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Cyberneurova GLM 5.3 Flash BF16 by cyberneurova — VRAM 471.3GB

Name: Cyberneurova GLM 5.3 Flash BF16
Author: cyberneurova

Cyberneurova GLM 5.3 Flash BF16 is an open-source language model by cyberneurova. Features: 321.3b LLM, VRAM: 471.3GB, License: mit, LLM Explorer Score: 0.28.

Base model:finetune:zai-org/gl... Base model:zai-org/glm-5.3-fla... Bf16 Conversational Cyberneurova Endpoints compatible Glm5 next Image-text-to-text Moe Reasoning Region:us Safetensors Sharded Tensorflow Uncensored

Model Card on HF 🤗: https://huggingface.co/cyberneurova/cyberneurova-GLM-5.3-Flash-BF16

Cyberneurova GLM 5.3 Flash BF16 Parameters and Internals

LLM Name	Cyberneurova GLM 5.3 Flash BF16
Repository 🤗	https://huggingface.co/cyberneurova/cyberneurova-GLM-5.3-Flash-BF16
Base Model(s)	zai-org/GLM-5.3-Flash zai-org/GLM-5.3-Flash
Model Size	321.3b
Required VRAM	471.3 GB
Updated	2026-09-20
Maintainer	cyberneurova
Model Type	glm5_next
Model Files	8.1 GB: 1-of-62 10.2 GB: 2-of-62 10.5 GB: 3-of-62 10.4 GB: 4-of-62 10.7 GB: 5-of-62 10.7 GB: 6-of-62 10.4 GB: 7-of-62 10.4 GB: 8-of-62 10.7 GB: 9-of-62 10.4 GB: 10-of-62 10.7 GB: 11-of-62 10.4 GB: 12-of-62 10.7 GB: 13-of-62 10.4 GB: 14-of-62 10.4 GB: 15-of-62 10.7 GB: 16-of-62 10.4 GB: 17-of-62 10.4 GB: 18-of-62 10.4 GB: 19-of-62 10.7 GB: 20-of-62 10.4 GB: 21-of-62 10.7 GB: 22-of-62 10.7 GB: 23-of-62 10.4 GB: 24-of-62 10.4 GB: 25-of-62 10.4 GB: 26-of-62 10.7 GB: 27-of-62 10.7 GB: 28-of-62 10.4 GB: 29-of-62 10.7 GB: 30-of-62 10.4 GB: 31-of-62 10.7 GB: 32-of-62 10.4 GB: 33-of-62 10.7 GB: 34-of-62 10.7 GB: 35-of-62 10.4 GB: 36-of-62 10.7 GB: 37-of-62 10.4 GB: 38-of-62 10.4 GB: 39-of-62 10.7 GB: 40-of-62 10.7 GB: 41-of-62 10.4 GB: 42-of-62 10.4 GB: 43-of-62 10.7 GB: 44-of-62 10.4 GB: 45-of-62
Model Architecture	Glm5NextForConditionalGeneration
License	mit
Transformers Version	5.16.0
Torch Data Type	bfloat16

Rank the Cyberneurova GLM 5.3 Flash BF16 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 Cyberneurova GLM 5.3 Flash BF16

Best Alternatives	Context / RAM	Downloads	Likes
GLM 5.3 Flash	0K / 237.5 GB	34	1289
GLM 5.3 Flash BF16	0K / 237.1 GB	24	38
GLM 5.3 Flash FP8	0K / 237.5 GB	5048	22
... 5.3 Flash CYBERSECURITY W4A16	0K / 71.6 GB	4022	8
GLM 5.3 Flash ABLITERATED FP8	0K / 226.7 GB	1465	18
GLM 5.3 Flash	0K / 242.5 GB	1034	15
GLM 5.3 Flash Nota NVFP4	0K / 21 GB	160	17
Cyberneurova GLM 5.3 Flash FP8	0K / 242.9 GB	183	2
GLM 5.3 Flash DERISKED BF16	0K / 237.1 GB	282	4
...Flash MXFP4 Mixed CT AutoRound	0K / 67.4 GB	195	1

Note: green Score (e.g. "73.2") means that the model is better than cyberneurova/cyberneurova-GLM-5.3-Flash-BF16.