What are the hardware requirements for LLaMA Mesh?

LLaMA Mesh 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 LLaMA Mesh and how large is it?

LLaMA Mesh is developed by Zhengyi, 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 LLaMA Mesh?

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

LLaMA Mesh by Zhengyi — VRAM 16.1GB, 128K context

Name: LLaMA Mesh
Author: Zhengyi

LLaMA Mesh is an open-source language model by Zhengyi. Features: 8b LLM, VRAM: 16.1GB, Context: 128K, License: llama3.1, LLM Explorer Score: 0.17.

Arxiv:2411.09595 Deploy:azure Endpoints compatible Llama Mesh-generation Region:us Safetensors Sharded Tensorflow Text-to-3d

Model Card on HF 🤗: https://huggingface.co/Zhengyi/LLaMA-Mesh

LLaMA Mesh Parameters and Internals

Model Type

3D Mesh Generation, Text Generation

Additional Notes

This model aims to unify 3D and text modalities into one system, allowing for simultaneous generation and comprehension of both text and 3D mesh data.

Training Details

Data Sources:

Objaverse

Data Volume:

30k mesh data, subset from Objaverse

Methodology:

Supervised fine-tuning using text and 3D interleaved data

Context Length:

8000

Hardware Used:

32 GPUs

Model Architecture:

Transformer

Input Output

Input Format:

String

Accepted Modalities:

Text

Output Format:

String

LLM Name	LLaMA Mesh
Repository 🤗	https://huggingface.co/Zhengyi/LLaMA-Mesh
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-07-12
Maintainer	Zhengyi
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
License	llama3.1
Context Length	131072
Model Max Length	131072
Transformers Version	4.44.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|eot_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the LLaMA Mesh 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 LLaMA Mesh

Best Alternatives	Context / RAM	Downloads	Likes
LWM Text 512K	512K / 13.5 GB	13	2
LWM Text Chat 512K	512K / 13.5 GB	9	2
LWM Text Chat 256K	256K / 13.5 GB	10	3
LWM Text 256K	256K / 13.5 GB	5	3
Pallas 0.5 LASER 0.1	195K / 68.9 GB	52	2
SnorTTS Indic V0	128K / 9.5 GB	518	22
Orpheus AUS	128K / GB	18	0
Finetuning Health Ci	128K / 6.5 GB	23	2
Ukr Synth Phi 3.5	128K / 7.6 GB	9	0
WizardLM Phi 3.5	128K / 7.6 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than Zhengyi/LLaMA-Mesh.