What are the hardware requirements for S5 Nano?

S5 Nano requires approximately 9.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed S5 Nano and how large is it?

S5 Nano is developed by maritaca-ai, a model with 4.7b 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 S5 Nano?

S5 Nano is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

S5 Nano by maritaca-ai — VRAM 9.3GB

Name: S5 Nano
Author: maritaca-ai

S5 Nano is an open-source language model by maritaca-ai. Features: 4.7b LLM, VRAM: 9.3GB, License: apache-2.0, LLM Explorer Score: 0.42.

Conversational En Endpoints compatible Image-text-to-text Pt Qwen3 5 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/maritaca-ai/S5-nano

S5 Nano Parameters and Internals

LLM Name	S5 Nano
Repository 🤗	https://huggingface.co/maritaca-ai/S5-nano
Model Size	4.7b
Required VRAM	9.3 GB
Updated	2026-11-09
Maintainer	maritaca-ai
Model Type	qwen3_5
Model Files	5.0 GB: 1-of-2 4.3 GB: 2-of-2
Supported Languages	pt en
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	4.57.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the S5 Nano 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 S5 Nano

Best Alternatives	Context / RAM	Downloads	Likes
Chandra Ocr 2 MTP Repacked	0K / 9.3 GB	903	1
Qwen Finetune1 16bit	0K / 9.3 GB	96	0