What are the hardware requirements for ILLaDA 8B Base?

ILLaDA 8B Base requires approximately 16.5 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed ILLaDA 8B Base and how large is it?

ILLaDA 8B Base is developed by GSAI-ML, 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 ILLaDA 8B Base?

ILLaDA 8B Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

ILLaDA 8B Base by GSAI-ML — VRAM 16.5GB, 8K context

Name: ILLaDA 8B Base
Author: GSAI-ML

ILLaDA 8B Base is an open-source language model by GSAI-ML. Features: 8b LLM, VRAM: 16.5GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.26.

Arxiv:2606.25331 Conversational Custom code Feature-extraction Illada Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/GSAI-ML/iLLaDA-8B-Base

ILLaDA 8B Base Parameters and Internals

LLM Name	ILLaDA 8B Base
Repository 🤗	https://huggingface.co/GSAI-ML/iLLaDA-8B-Base
Model Size	8b
Required VRAM	16.5 GB
Updated	2026-10-30
Maintainer	GSAI-ML
Model Type	illada
Model Files	5.0 GB: 1-of-4 4.9 GB: 2-of-4 5.0 GB: 3-of-4 1.6 GB: 4-of-4
Model Architecture	ILLaDAForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.57.1
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<[PAD]>
Vocabulary Size	155136
Torch Data Type	bfloat16

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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