{"data":{"slug":"nvlabs-eagle","name":"Eagle","tagline":"Frontier Vision-Language Models with Data-Centric Strategies","github_url":"https://github.com/NVlabs/Eagle","owner":"NVlabs","repo":"Eagle","owner_avatar_url":"https://avatars.githubusercontent.com/u/2695301?v=4","primary_language":"Python","stars":3407,"forks":327,"topics":["demo","eagle","gpt4","huggingface","large-language-models","llama","llama3","llava","llm","lmm","lvlm","mllm","nvdia"],"archived":false,"github_pushed_at":"2026-06-24T18:12:11+00:00","maintenance_label":"Steady","stars_delta_30d":199,"url":"https://www.graphcanon.com/tools/nvlabs-eagle","markdown_url":"https://www.graphcanon.com/tools/nvlabs-eagle.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/nvlabs-eagle","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=nvlabs-eagle","description":"Eagle: Frontier Vision-Language Models with Data-Centric Strategies","homepage_url":"https://nvlabs.github.io/Eagle/","license":"Apache-2.0","open_issues":62,"watchers":37,"ai_summary":"Eagle is a repository for vision-language models developed by NVlabs using data-centric strategies, incorporating improvements from Qwen. The project includes pretrained model weights licensed under CC BY-NC 4.0 and the NVIDIA License.","readme_excerpt":"## License/Terms of Use\n- The code is released under the Apache 2.0 license as found in the [LICENSE](./LICENSE) file. Portions of the code in this repo are reused and subject to their original licenses. Some files have been modified, with appropriate attribution and additional license headers added where applicable.\n- The pretrained model weights are released under either the [CC BY-NC 4.0 License](https://creativecommons.org/licenses/by-nc/4.0/deed.en) or the [NVIDIA License](./Eagle2_5/LICENSE_MODEL). The models are research preview intended for non-commercial use only.\n- Eagle models are improved using Qwen.\n- For code contributions to Eagle, please refer to the [Contribution Guide](CONTRIBUTING.md).\n- Users are reminded to ensure that their use of the dataset and model weights is in compliance with all applicable laws and regulations.","github_created_at":"2024-06-27T07:22:52+00:00","created_at":"2026-07-11T11:06:31.12779+00:00","updated_at":"2026-09-20T05:36:21.126396+00:00","categories":[{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"data-centric-strategies","name":"data-centric-strategies"},{"slug":"gpt4","name":"gpt4"},{"slug":"huggingface","name":"huggingface"},{"slug":"llm-improvements","name":"llm-improvements"},{"slug":"nvidia-technology","name":"nvidia-technology"},{"slug":"vision-language-models","name":"vision-language-models"}],"trust":{"provenance":{"is_fork":false,"github_id":820789280,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-18T00:02:04.616Z","maintenance":{"label":"Steady","score":60,"methodology":"github_public_v1","releases_90d":0,"days_since_push":54,"last_release_at":null,"stars_delta_30d":199,"open_issues_delta_30d":3},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:06:32.491Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-18T00:02:05.041Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-08-18T00:02:05.041Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-18T00:02:05.041Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"Free for non-commercial use; requires adherence to licensing agreements"},"requirements":{"notes":["Ensure compliance with all applicable laws and regulations when using the dataset and model weights."],"min_ram_gb":8,"requires_docker":false},"constraints":{"min_ram_gb":8,"pricing_model":"freemium","requires_docker":false},"when_to_use":["When you need advanced vision-language models enhanced by data-centric strategies developed by NVlabs and improved using Qwen.","For non-commercial research purposes where Apache-2.0 licensed code and CC BY-NC 4.0 or NVIDIA-licensed model weights are acceptable."],"when_not_to_use":["If your project requires commercial use, as Eagle's models are intended for non-commercial use only under the CC BY-NC 4.0 License or NVIDIA License.","In situations where you require a vision-language model that does not rely on improvements made using Qwen."],"source":"enrich:decision_facts","observed_at":"2026-07-12T18:12:08.189Z"},"constraint_facets":{"min_ram_gb":8,"pricing_model":"freemium","requires_docker":false},"decision_summary":[{"label":"Pricing","value":"freemium - Free for non-commercial use; requires adherence to licensing agreements"},{"label":"Requirements","value":"Min 8 GB RAM; Ensure compliance with all applicable laws and regulations when using the dataset and model weights."},{"label":"Adopt for","value":"Eagle: Frontier Vision-Language Models with Data-Centric Strategies"},{"label":"License detail","value":"The code is released under Apache 2.0 license, while the pretrained models are under CC BY-NC 4.0 or NVIDIA licenses for non-commercial use only."}]}}