--- title: "VLN-CE vs Eagle" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/jacobkrantz-vln-ce-vs-nvlabs-eagle" tools: ["jacobkrantz-vln-ce", "nvlabs-eagle"] --- # VLN-CE vs Eagle *GraphCanon updated Aug 18, 2026* ## Verdict Pick VLN-CE if vLN-CE provides Python-based resources for Vision-and-Language Navigation research using Habitat. It uses the MIT license but the datasets adhere to Matterport3D terms; pick Eagle if eagle: Frontier Vision-Language Models with Data-Centric Strategies. [VLN-CE](https://jacobkrantz.github.io/vlnce/) reports 844 GitHub stars, 90 forks, and 29 open issues, last pushed Jan 7, 2025. [Eagle](https://nvlabs.github.io/Eagle/) has 3.4k stars, 327 forks, and 62 open issues, last pushed Jun 24, 2026. Figures are from public GitHub metadata via [VLN-CE's repository](https://github.com/jacobkrantz/VLN-CE) and [Eagle's repository](https://github.com/NVlabs/Eagle). | | [VLN-CE](/tools/jacobkrantz-vln-ce.md) | [Eagle](/tools/nvlabs-eagle.md) | | --- | --- | --- | | Tagline | Vision-and-Language Navigation in Continuous Environments using Habitat | Frontier Vision-Language Models with Data-Centric Strategies | | Stars | 844 | 3,407 | | Forks | 90 | 327 | | Open issues | 29 | 62 | | Language | Python | Python | | Adopt for | VLN-CE provides Python-based resources for Vision-and-Language Navigation research using Habitat. It uses the MIT license but the datasets adhere to Matterport3D terms. | Eagle: Frontier Vision-Language Models with Data-Centric Strategies | | Persona | - | - | | Runtime | - | - | | License | MIT | 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. | | Categories | Computer Vision, Model Training | Computer Vision, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [VLN-CE](/tools/jacobkrantz-vln-ce.md) | [Eagle](/tools/nvlabs-eagle.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 569d | 54d | | Open issues (now) | 29 | 62 | | Stars delta | Unknown | +199 (30d) | | Open issues delta | Unknown | +3 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/jacobkrantz-vln-ce/trust.md) | [trust report](/tools/nvlabs-eagle/trust.md) | ## Decision facts: VLN-CE - **Adopt for:** VLN-CE provides Python-based resources for Vision-and-Language Navigation research using Habitat. It uses the MIT license but the datasets adhere to Matterport3D terms. ## Decision facts: Eagle - **Pricing:** freemium - Free for non-commercial use; requires adherence to licensing agreements - **Requirements:** Min 8 GB RAM; Ensure compliance with all applicable laws and regulations when using the dataset and model weights. - **Adopt for:** Eagle: Frontier Vision-Language Models with Data-Centric Strategies - **License detail:** 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. ## Choose when ### Choose VLN-CE if… - License: VLN-CE is MIT, Eagle is Apache-2.0. - Tags unique to VLN-CE: ai, computer-vision, deep-learning, python. - Also covers Model Training. - When aiming to advance robotics navigation by training models on vision-language tasks with habitat-sim. ### Choose Eagle if… - License: Eagle is Apache-2.0, VLN-CE is MIT. - Pricing: Free for non-commercial use; requires adherence to licensing agreements. - Requirements: Min 8 GB RAM; Ensure compliance with all applicable laws and regulations when using the dataset and model weights.. - Tags unique to Eagle: data-centric-strategies, gpt4, huggingface, llm-improvements. - Also covers LLM Frameworks. - When you need advanced vision-language models enhanced by data-centric strategies developed by NVlabs and improved using Qwen. ## When NOT to use VLN-CE - Avoid if your project needs fully open datasets, as some VLN-CE components are restricted by Matterport3D license terms. - Steer clear if you prefer tools with built-in support for environments other than those within the Habitat simulation framework. ## When NOT to use Eagle - 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. ## Common questions ### What is the difference between VLN-CE and Eagle? VLN-CE: Vision-and-Language Navigation in Continuous Environments using Habitat. Eagle: Frontier Vision-Language Models with Data-Centric Strategies. See the comparison table for live GitHub stats and shared categories. ### When should I choose VLN-CE over Eagle? Choose VLN-CE over Eagle when License: VLN-CE is MIT, Eagle is Apache-2.0; Tags unique to VLN-CE: ai, computer-vision, deep-learning, python; Also covers Model Training; When aiming to advance robotics navigation by training models on vision-language tasks with habitat-sim. ### When should I choose Eagle over VLN-CE? Choose Eagle over VLN-CE when License: Eagle is Apache-2.0, VLN-CE is MIT; Pricing: Free for non-commercial use; requires adherence to licensing agreements; Requirements: Min 8 GB RAM; Ensure compliance with all applicable laws and regulations when using the dataset and model weights.; Tags unique to Eagle: data-centric-strategies, gpt4, huggingface, llm-improvements; Also covers LLM Frameworks; When you need advanced vision-language models enhanced by data-centric strategies developed by NVlabs and improved using Qwen. ### When should I avoid VLN-CE? Avoid if your project needs fully open datasets, as some VLN-CE components are restricted by Matterport3D license terms. Steer clear if you prefer tools with built-in support for environments other than those within the Habitat simulation framework. ### When should I avoid Eagle? 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. ### Is VLN-CE or Eagle more popular on GitHub? Eagle has more GitHub stars (3,407 vs 844). Stars measure visibility, not whether either tool fits your constraints. ### Are VLN-CE and Eagle open source? Yes - both are open-source projects on GitHub (VLN-CE: MIT, Eagle: Apache-2.0). ### Where can I find alternatives to VLN-CE or Eagle? GraphCanon lists graph-backed alternatives at [VLN-CE alternatives](/tools/jacobkrantz-vln-ce/alternatives) and [Eagle alternatives](/tools/nvlabs-eagle/alternatives) ([VLN-CE markdown twin](/tools/jacobkrantz-vln-ce/alternatives.md), [Eagle markdown twin](/tools/nvlabs-eagle/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/jacobkrantz-vln-ce-vs-nvlabs-eagle.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, VLN-CE or Eagle? VLN-CE: Dormant. Eagle: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for VLN-CE and Eagle? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [VLN-CE trust report](/tools/jacobkrantz-vln-ce/trust); [Eagle trust report](/tools/nvlabs-eagle/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=jacobkrantz-vln-ce`](/api/graphcanon/graph?tool=jacobkrantz-vln-ce) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_