InternRobotics/PointLLM

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1051 stars · 58 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

PointLLM is a multimodal large language model that understands colored 3D point clouds of objects, built on a point cloud encoder fused with an LLM (LLaMA-based). It ships with a 660K+70K point-text instruction dataset, two-stage training code, and benchmarks for generative 3D classification and captioning.

Use cases

• chat with an LLM about 3D point clouds of objects
• generate captions describing 3D object point clouds
• classify 3D objects generatively from point clouds
• train a multimodal LLM on point-text instruction data
• evaluate 3D perception of large language models
• understand geometry and appearance without depth ambiguity

When to choose

• you need LLM-based understanding of raw 3D point clouds rather than 2D images
• you want a research foundation model and benchmark for 3D-language tasks
• you have point cloud data and want instruction-following dialogue or captioning

When to avoid

• you need production-ready, commercially licensed software (no license is provided)
• you lack GPU resources for large multimodal model inference or training
• you need 2D image or video understanding rather than point clouds

Facets

library · maturity active

llm-inference machine-learning nlp computer-vision chatbot large-language-models computer-vision artificial-intelligence deep-learning python point-cloud multimodal 3d-understanding instruction-tuning llama research-model eccv-2024 gpu linux

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markdown · JSON · MCP: product_card(name="InternRobotics/PointLLM")