Awesome-LLM-3D

Overview

A curated GitHub repository listing resources (papers, code, datasets) for multi-modal large language models in the 3D domain. It serves as a reference index for researchers and developers working at the intersection of LLMs and 3D understanding.

Best for

Best for
Researchers and engineers exploring the intersection of large language models and 3D understanding

Use cases

• Discovering recent papers and codebases on 3D-aware LLMs
• Finding benchmark datasets for evaluating 3D multimodal models
• Tracking community progress in 3D vision-language research

Notes

A curated GitHub repository listing resources (papers, code, datasets) for multi-modal large language models in the 3D domain. It serves as a reference index for researchers and developers working at the intersection of LLMs and 3D understanding.

2,212 stars on GitHub. Last updated 2026-04-16. Licensed MIT.

Use cases

• Discovering recent papers and codebases on 3D-aware LLMs
• Finding benchmark datasets for evaluating 3D multimodal models
• Tracking community progress in 3D vision-language research

Pros

• Comprehensive collection of 2,200+ stars indicates broad community trust
• Covers papers, code, and datasets in one place
• Regularly updated by the Active Vision Lab community

Cons

• Not a runnable tool or library; requires manual navigation
• May lack detailed documentation or usage examples for each resource
• Relies on community contributions, so some entries may become stale

Indexed from awesome-llm and enriched against its public facts.