What are the hardware requirements for Laguna S 2.1 NVFP4 W4A16 Quality?

Laguna S 2.1 NVFP4 W4A16 Quality requires approximately 92.5 GB of VRAM and supports a context window of 1024K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Laguna S 2.1 NVFP4 W4A16 Quality and how large is it?

Laguna S 2.1 NVFP4 W4A16 Quality is developed by jackzampolin, a model with 70.5b 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 Laguna S 2.1 NVFP4 W4A16 Quality?

Laguna S 2.1 NVFP4 W4A16 Quality is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Laguna S 2.1 NVFP4 W4A16 Quality by jackzampolin — VRAM 92.5GB, 1024K context

Name: Laguna S 2.1 NVFP4 W4A16 Quality
Author: jackzampolin

Laguna S 2.1 NVFP4 W4A16 Quality is an open-source language model by jackzampolin. Features: 70.5b LLM, VRAM: 92.5GB, Context: 1024K, License: openmdw-1.1, LLM Explorer Score: 0.27.

8-bit Base model:poolside/laguna-s-2... Base model:quantized:poolside/... Conversational Custom code Endpoints compatible Fp8 Laguna Modelopt Nvfp4 Quantized Region:us Safetensors Sharded Tensorflow Vllm W4a16

Model Card on HF 🤗: https://huggingface.co/jackzampolin/Laguna-S-2.1-NVFP4-W4A16-Quality

Laguna S 2.1 NVFP4 W4A16 Quality Parameters and Internals

LLM Name	Laguna S 2.1 NVFP4 W4A16 Quality
Repository 🤗	https://huggingface.co/jackzampolin/Laguna-S-2.1-NVFP4-W4A16-Quality
Base Model(s)	poolside/Laguna-S-2.1 poolside/Laguna-S-2.1
Model Size	70.5b
Required VRAM	92.5 GB
Updated	2026-08-06
Maintainer	jackzampolin
Model Type	laguna
Model Files	10.0 GB: 1-of-10 10.0 GB: 2-of-10 10.0 GB: 3-of-10 10.0 GB: 4-of-10 10.0 GB: 5-of-10 10.0 GB: 6-of-10 10.0 GB: 7-of-10 10.0 GB: 8-of-10 10.0 GB: 9-of-10 2.5 GB: 10-of-10
Model Architecture	LagunaForCausalLM
License	openmdw-1.1
Context Length	1048576
Model Max Length	1048576
Transformers Version	5.14.1
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	〈\|PAD\|〉
Vocabulary Size	100352

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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