What are the hardware requirements for LWM Text 256K GGUF?

LWM Text 256K GGUF requires approximately 2.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed LWM Text 256K GGUF and how large is it?

LWM Text 256K GGUF is developed by MaziyarPanahi. 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 LWM Text 256K GGUF?

LWM Text 256K GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

LWM Text 256K GGUF by MaziyarPanahi — VRAM 2.5GB

Name: LWM Text 256K GGUF
Author: MaziyarPanahi

LWM Text 256K GGUF is an open-source language model by MaziyarPanahi. Features: LLM, VRAM: 2.5GB, Quantized, LLM Explorer Score: 0.11.

2-bit 3-bit 4-bit 5-bit 6-bit 8-bit Autotrain compatible Base model:largeworldmodel/lwm... Base model:quantized:largeworl... Gguf Llama Mistral Pytorch Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/MaziyarPanahi/LWM-Text-256K-GGUF

LWM Text 256K GGUF Parameters and Internals

Model Type

text-generation

LLM Name	LWM Text 256K GGUF
Repository 🤗	https://huggingface.co/MaziyarPanahi/LWM-Text-256K-GGUF
Model Name	LWM-Text-256K-GGUF
Model Creator	LargeWorldModel
Base Model(s)	LWM Text 256K LargeWorldModel/LWM-Text-256K
Required VRAM	2.5 GB
Updated	2026-08-07
Maintainer	MaziyarPanahi
Model Type	mistral
Model Files	2.5 GB 3.6 GB 3.3 GB 3.0 GB 4.1 GB 3.9 GB 4.8 GB 4.7 GB 5.5 GB 7.2 GB 13.5 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel

Rank the LWM Text 256K GGUF 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

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Note: green Score (e.g. "73.2") means that the model is better than MaziyarPanahi/LWM-Text-256K-GGUF.