What are the hardware requirements for Cyber F1?

Cyber F1 requires approximately 70.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Cyber F1 and how large is it?

Cyber F1 is developed by DuyTa, a model with 35.1b 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 Cyber F1?

Cyber F1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Cyber F1 by DuyTa — VRAM 70.6GB

Name: Cyber F1
Author: DuyTa

Cyber F1 is an open-source language model by DuyTa. Features: 35.1b LLM, VRAM: 70.6GB, License: mit, LLM Explorer Score: 0.25.

Qwen3 5 moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/DuyTa/Cyber-F1

Cyber F1 Parameters and Internals

LLM Name	Cyber F1
Repository 🤗	https://huggingface.co/DuyTa/Cyber-F1
Model Size	35.1b
Required VRAM	70.6 GB
Updated	2026-09-20
Maintainer	DuyTa
Model Type	qwen3_5_moe
Model Files	5.4 GB: 0-of-14 5.4 GB: 1-of-14 5.4 GB: 2-of-14 5.4 GB: 3-of-14 5.4 GB: 4-of-14 5.4 GB: 5-of-14 5.4 GB: 6-of-14 5.4 GB: 7-of-14 5.4 GB: 8-of-14 5.4 GB: 9-of-14 5.4 GB: 10-of-14 5.4 GB: 11-of-14 5.4 GB: 12-of-14 0.4 GB: 13-of-14
Model Architecture	Qwen3_5MoeForConditionalGeneration
License	mit
Model Max Length	262144
Transformers Version	4.57.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Cyber F1 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 Cyber F1

Best Alternatives	Context / RAM	Downloads	Likes
Nex N2.5 Mini	0K / 70.4 GB	3121	685
Agents A1	0K / 70.6 GB	23272	629
Nex N2 Mini	0K / 70.4 GB	2289	294
Thomson 1.0 Small	0K / 70.5 GB	214	109
Nex N2 Mini	0K / 70.4 GB	210	1
Huihui Agents A1 Abliterated	0K / 70.6 GB	3339	29
Occamy 1.0 FP8	0K / 36.8 GB	324	4
...yJ5ua3Sebfyr8kcVwLAdaiJLUC8pkW	0K / 70.4 GB	1894	0
Affine 5g4yy75zuz T6	0K / 70.2 GB	756	0
Affine 5efg6cm3yl King	0K / 70.3 GB	578	0

Note: green Score (e.g. "73.2") means that the model is better than DuyTa/Cyber-F1.