NVlabs/Eagle

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3462 stars · 334 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Eagle is NVIDIA's family of frontier vision-language models (Eagle, Eagle 2, Eagle 2.5) built with data-centric training strategies, plus LocateAnything, a visual grounding model. The repo provides training, fine-tuning, and inference code along with model weights on Hugging Face.

Use cases

• run a vision-language model on images and videos
• fine-tune a VLM with LoRA for visual grounding
• understand long videos with a multimodal model
• use a VLM as a backbone for a robotics policy
• build an image and video chat demo
• train a multimodal LLM with data-centric strategies

When to choose

• you need open weights and code for a state-of-the-art VLM
• you want long-context image/video understanding
• you need a VLM backbone for embodied or robotics research
• you want visual grounding / object localization capabilities

When to avoid

• you need a lightweight model for CPU-only deployment
• you only want a hosted API without managing GPUs
• you need non-Apache model licensing terms for commercial use

Facets

library · maturity active

machine-learning deep-learning llm-training computer-vision nlp large-language-models computer-vision deep-learning machine-learning artificial-intelligence python vision-language-model multimodal vlm video-understanding visual-grounding model-weights nvidia fine-tuning lora huggingface gpu linux docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="NVlabs/Eagle")