What are the hardware requirements for Slu 35?

Slu 35 requires approximately 16.1 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Slu 35 and how large is it?

Slu 35 is developed by jaspionjader, 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 Slu 35?

Slu 35 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Slu 35 by jaspionjader — VRAM 16.1GB, 128K context

Name: Slu 35
Author: jaspionjader

Slu 35 is an open-source language model by jaspionjader. Features: 8b LLM, VRAM: 16.1GB, Context: 128K, Merged, LLM Explorer Score: 0.22.

Merged Model Arxiv:2403.19522 Base model:jaspionjader/slu-29 Base model:jaspionjader/slu-33 Base model:jaspionjader/slu-34 Conversational Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/jaspionjader/slu-35

Slu 35 Parameters and Internals

LLM Name	Slu 35
Repository 🤗	https://huggingface.co/jaspionjader/slu-35
Base Model(s)	Slu 29 Slu 33 Slu 34 jaspionjader/slu-29 jaspionjader/slu-33 jaspionjader/slu-34
Merged Model	Yes
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-07-17
Maintainer	jaspionjader
Model Type	llama
Model Files	5.0 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.2 GB: 4-of-4
Model Architecture	LlamaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.46.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|eot_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Slu 35 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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