What are the hardware requirements for Laguna S 2.1 MLX 6bit?

Laguna S 2.1 MLX 6bit requires approximately 95.4 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 MLX 6bit and how large is it?

Laguna S 2.1 MLX 6bit is developed by pipenetwork, a model with 117.6b 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 MLX 6bit?

Laguna S 2.1 MLX 6bit 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 MLX 6bit by pipenetwork — VRAM 95.4GB, 1024K context

Name: Laguna S 2.1 MLX 6bit
Author: pipenetwork

Laguna S 2.1 MLX 6bit is an open-source language model by pipenetwork. Features: 117.6b LLM, VRAM: 95.4GB, Context: 1024K, License: openmdw-1.1, Quantized, LLM Explorer Score: 0.29.

6-bit 6bit Base model:poolside/laguna-s-2... Base model:quantized:poolside/... Code Conversational Custom code Laguna Mlx Moe Poolside Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/pipenetwork/Laguna-S-2.1-MLX-6bit

Laguna S 2.1 MLX 6bit Parameters and Internals

LLM Name	Laguna S 2.1 MLX 6bit
Repository 🤗	https://huggingface.co/pipenetwork/Laguna-S-2.1-MLX-6bit
Base Model(s)	poolside/Laguna-S-2.1 poolside/Laguna-S-2.1
Model Size	117.6b
Required VRAM	95.4 GB
Updated	2026-07-23
Maintainer	pipenetwork
Model Type	laguna
Model Files	5.1 GB: 1-of-19 5.4 GB: 2-of-19 5.3 GB: 3-of-19 4.8 GB: 4-of-19 5.3 GB: 5-of-19 5.3 GB: 6-of-19 5.3 GB: 7-of-19 4.8 GB: 8-of-19 5.4 GB: 9-of-19 5.4 GB: 10-of-19 4.8 GB: 11-of-19 5.3 GB: 12-of-19 5.3 GB: 13-of-19 5.4 GB: 14-of-19 4.8 GB: 15-of-19 5.4 GB: 16-of-19 5.3 GB: 17-of-19 4.8 GB: 18-of-19 2.2 GB: 19-of-19
Quantization Type	6bit
Model Architecture	LagunaForCausalLM
License	openmdw-1.1
Context Length	1048576
Model Max Length	1048576
Tokenizer Class	TokenizersBackend
Padding Token	〈\|PAD\|〉
Vocabulary Size	100352
Torch Data Type	bfloat16

Rank the Laguna S 2.1 MLX 6bit capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to Laguna S 2.1 MLX 6bit

Best Alternatives	Context / RAM	Downloads	Likes
Laguna S 2.1 OptiQ 2bit	1024K / 44.2 GB	380	2
Laguna S 2.1 MLX 4bit	1024K / 65.8 GB	493	3
Laguna S 2.1	1024K / 214.2 GB	56445	708
Laguna S 2.1 INT4	1024K / 100.2 GB	191066	26
Laguna S 2.1 FP8	1024K / 116.8 GB	53942	26
Laguna S 2.1	1024K / 214.2 GB	569	7
Laguna S 2.1 AWQ INT4	1024K / 78.2 GB	533	4
Laguna S 2.1 Heretic	1024K / 219.3 GB	45	0

Note: green Score (e.g. "73.2") means that the model is better than pipenetwork/Laguna-S-2.1-MLX-6bit.