--- title: "Aquila2 vs Eagle" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/flagai-open-aquila2-vs-nvlabs-eagle" tools: ["flagai-open-aquila2", "nvlabs-eagle"] --- # Aquila2 vs Eagle *GraphCanon updated Aug 25, 2026* ## Verdict Pick Aquila2 if official suite for Aquila2 series LLM by BAAI; pick Eagle if eagle: Frontier Vision-Language Models with Data-Centric Strategies. [Aquila2](https://github.com/FlagAI-Open/Aquila2) reports 447 GitHub stars, 32 forks, and 2 open issues, last pushed Oct 11, 2024. [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 [Aquila2's repository](https://github.com/FlagAI-Open/Aquila2) and [Eagle's repository](https://github.com/NVlabs/Eagle). | | [Aquila2](/tools/flagai-open-aquila2.md) | [Eagle](/tools/nvlabs-eagle.md) | | --- | --- | --- | | Tagline | Official repository for Aquila2 series large language models by BAAI | Frontier Vision-Language Models with Data-Centric Strategies | | Stars | 447 | 3,407 | | Forks | 32 | 327 | | Open issues | 2 | 62 | | Language | Python | Python | | Adopt for | Official suite for Aquila2 series LLM by BAAI | Eagle: Frontier Vision-Language Models with Data-Centric Strategies | | Persona | - | - | | Runtime | - | - | | License | (unknown) | 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 | Inference & Serving, LLM Frameworks, Model Training | Computer Vision, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Aquila2](/tools/flagai-open-aquila2.md) | [Eagle](/tools/nvlabs-eagle.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 683d | 54d | | Open issues (now) | 2 | 62 | | Stars delta | +1 (30d) | +199 (30d) | | Open issues delta | 0 (30d) | +3 (30d) | | Full report | [trust report](/tools/flagai-open-aquila2/trust.md) | [trust report](/tools/nvlabs-eagle/trust.md) | ## Decision facts: Aquila2 - **Adopt for:** Official suite for Aquila2 series LLM by BAAI - **License detail:** (unknown) ## 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 Aquila2 if… - Tags unique to Aquila2: llm, llm-inference, llm-training. - Also covers Inference & Serving, Model Training. - Need specialized support from Beijing Academy of Artificial Intelligence ### Choose Eagle if… - 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 Computer Vision. - When you need advanced vision-language models enhanced by data-centric strategies developed by NVlabs and improved using Qwen. ## When NOT to use Aquila2 - Require comprehensive API and documentation clarity - Preferring open source licensing details ## 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 Aquila2 and Eagle? Aquila2: Official repository for Aquila2 series large language models by BAAI. Eagle: Frontier Vision-Language Models with Data-Centric Strategies. See the comparison table for live GitHub stats and shared categories. ### When should I choose Aquila2 over Eagle? Choose Aquila2 over Eagle when Tags unique to Aquila2: llm, llm-inference, llm-training; Also covers Inference & Serving, Model Training; Need specialized support from Beijing Academy of Artificial Intelligence. ### When should I choose Eagle over Aquila2? Choose Eagle over Aquila2 when 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 Computer Vision; When you need advanced vision-language models enhanced by data-centric strategies developed by NVlabs and improved using Qwen. ### When should I avoid Aquila2? Require comprehensive API and documentation clarity Preferring open source licensing details ### 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 Aquila2 or Eagle more popular on GitHub? Eagle has more GitHub stars (3,407 vs 447). Stars measure visibility, not whether either tool fits your constraints. ### Are Aquila2 and Eagle open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to Aquila2 or Eagle? GraphCanon lists graph-backed alternatives at [Aquila2 alternatives](/tools/flagai-open-aquila2/alternatives) and [Eagle alternatives](/tools/nvlabs-eagle/alternatives) ([Aquila2 markdown twin](/tools/flagai-open-aquila2/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/flagai-open-aquila2-vs-nvlabs-eagle.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Aquila2 or Eagle? Aquila2: 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 Aquila2 and Eagle? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Aquila2 trust report](/tools/flagai-open-aquila2/trust); [Eagle trust report](/tools/nvlabs-eagle/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=flagai-open-aquila2`](/api/graphcanon/graph?tool=flagai-open-aquila2) - 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/_