What are the hardware requirements for Apertus V1.1 0.5B?

Apertus V1.1 0.5B requires approximately 0.9 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Apertus V1.1 0.5B and how large is it?

Apertus V1.1 0.5B is developed by swiss-ai, a model with 0.5b 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 Apertus V1.1 0.5B?

Apertus V1.1 0.5B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Apertus V1.1 0.5B by swiss-ai — VRAM 0.9GB, 4K context

Name: Apertus V1.1 0.5B
Author: swiss-ai

Apertus V1.1 0.5B is an open-source language model by swiss-ai. Features: 0.5b LLM, VRAM: 0.9GB, Context: 4K, License: apache-2.0, LLM Explorer Score: 0.25.

Arxiv:2509.14233 Arxiv:2605.29128 Apertus Compliant Endpoints compatible Multilingual Region:us Safetensors Swiss-ai

Model Card on HF 🤗: https://huggingface.co/swiss-ai/Apertus-v1.1-0.5B

Apertus V1.1 0.5B Parameters and Internals

LLM Name	Apertus V1.1 0.5B
Repository 🤗	https://huggingface.co/swiss-ai/Apertus-v1.1-0.5B
Model Size	0.5b
Required VRAM	0.9 GB
Updated	2026-08-02
Maintainer	swiss-ai
Model Type	apertus
Model Files	0.9 GB
Model Architecture	ApertusForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.57.6
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	131072

Rank the Apertus V1.1 0.5B 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

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