What are the hardware requirements for Apertus 1.5 8B Biomedical Ade?

Apertus 1.5 8B Biomedical Ade requires approximately 16.3 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Apertus 1.5 8B Biomedical Ade and how large is it?

Apertus 1.5 8B Biomedical Ade is developed by andreasmartin, a model with 8b 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 1.5 8B Biomedical Ade?

Apertus 1.5 8B Biomedical Ade is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Apertus 1.5 8B Biomedical Ade by andreasmartin — VRAM 16.3GB, 256K context

Name: Apertus 1.5 8B Biomedical Ade
Author: andreasmartin

Apertus 1.5 8B Biomedical Ade is an open-source language model by andreasmartin. Features: 8b LLM, VRAM: 16.3GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.32.

Adverse-drug-events Apertus Base model:andreasmartin/apert... Base model:finetune:andreasmar... Biomedical Conversational Dataset:mihirhirave/entity ext... En Endpoints compatible Named-entity-recognition Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/andreasmartin/apertus-1.5-8b-biomedical-ade

Apertus 1.5 8B Biomedical Ade Parameters and Internals

LLM Name	Apertus 1.5 8B Biomedical Ade
Repository 🤗	https://huggingface.co/andreasmartin/apertus-1.5-8b-biomedical-ade
Base Model(s)	andreasmartin/apertus-v1.5-8b-text andreasmartin/apertus-v1.5-8b-text
Model Size	8b
Required VRAM	16.3 GB
Updated	2026-09-07
Maintainer	andreasmartin
Model Type	apertus
Model Files	1.1 GB: 1-of-11 1.5 GB: 2-of-11 1.5 GB: 3-of-11 1.6 GB: 4-of-11 1.5 GB: 5-of-11 1.6 GB: 6-of-11 1.5 GB: 7-of-11 1.6 GB: 8-of-11 1.5 GB: 9-of-11 1.6 GB: 10-of-11 1.3 GB: 11-of-11
Supported Languages	en
Model Architecture	ApertusForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	131272
Torch Data Type	bfloat16

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Instruction Following and Task Automation
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Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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