--- title: "Aquila2 vs airllm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/flagai-open-aquila2-vs-lyogavin-airllm" tools: ["flagai-open-aquila2", "lyogavin-airllm"] --- # Aquila2 vs airllm *GraphCanon updated Sep 20, 2026* ## Verdict Pick Aquila2 if official suite for Aquila2 series LLM by BAAI; pick airllm if airLLM is a repository that enables the inference of a 70B parameter model using a single 4GB GPU, with a focus on Chinese language models and generative AI. [Aquila2](https://github.com/FlagAI-Open/Aquila2) reports 445 GitHub stars, 32 forks, and 2 open issues, last pushed Oct 11, 2024. [airllm](https://github.com/lyogavin/airllm) has 35k stars, 3.6k forks, and 155 open issues, last pushed Sep 18, 2026. Figures are from public GitHub metadata via [Aquila2's repository](https://github.com/FlagAI-Open/Aquila2) and [airllm's repository](https://github.com/lyogavin/airllm). | | [Aquila2](/tools/flagai-open-aquila2.md) | [airllm](/tools/lyogavin-airllm.md) | | --- | --- | --- | | Tagline | Official repository for Aquila2 series large language models by BAAI | Inference for AirLLM 70B model with single 4GB GPU | | Stars | 445 | 34,504 | | Forks | 32 | 3,626 | | Open issues | 2 | 155 | | Language | Python | Jupyter Notebook | | Adopt for | Official suite for Aquila2 series LLM by BAAI | AirLLM is a repository that enables the inference of a 70B parameter model using a single 4GB GPU, with a focus on Chinese language models and generative AI. | | Persona | - | - | | Runtime | - | - | | License | (unknown) | Apache-2.0 | | Categories | Inference & Serving, LLM Frameworks, Model Training | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Aquila2](/tools/flagai-open-aquila2.md) | [airllm](/tools/lyogavin-airllm.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 708d | 0d | | Open issues (now) | 2 | 155 | | Stars delta | -1 (30d) | +10k (30d) | | Open issues delta | 0 (30d) | +40 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/flagai-open-aquila2/trust.md) | [trust report](/tools/lyogavin-airllm/trust.md) | ## Shared compatibility - **Python**: [Aquila2](/tools/flagai-open-aquila2.md) - Python runtime; [airllm](/tools/lyogavin-airllm.md) - Python runtime ## Decision facts: Aquila2 - **Adopt for:** Official suite for Aquila2 series LLM by BAAI - **License detail:** (unknown) ## Decision facts: airllm - **Requirements:** Min 4 GB RAM; Installation is straightforward via pip. - **Adopt for:** AirLLM is a repository that enables the inference of a 70B parameter model using a single 4GB GPU, with a focus on Chinese language models and generative AI. - **License detail:** Apache-2.0 ## Choose when ### Choose Aquila2 if… - Aquila2 is primarily Python; airllm is Jupyter Notebook. - Tags unique to Aquila2: llm-inference, llm-training. - Also covers Model Training. - Need specialized support from Beijing Academy of Artificial Intelligence ### Choose airllm if… - airllm is primarily Jupyter Notebook; Aquila2 is Python. - Requirements: Min 4 GB RAM; Installation is straightforward via pip.. - Tags unique to airllm: chinese-llm, chinese-nlp, finetune, generative-ai. - When you need to perform inference on a 70B parameter model with limited GPU resources, such as a single 4GB GPU. ## When NOT to use Aquila2 - Require comprehensive API and documentation clarity - Preferring open source licensing details ## When NOT to use airllm - If your project requires inference on models larger than 70B parameters or if you have access to more powerful GPUs than a 4GB model. - For projects that do not involve Chinese language models or generative AI tasks, as AirLLM is specifically optimized for these areas. ## Common questions ### What is the difference between Aquila2 and airllm? Aquila2: Official repository for Aquila2 series large language models by BAAI. airllm: Inference for AirLLM 70B model with single 4GB GPU. See the comparison table for live GitHub stats and shared categories. ### When should I choose Aquila2 over airllm? Choose Aquila2 over airllm when Aquila2 is primarily Python; airllm is Jupyter Notebook; Tags unique to Aquila2: llm-inference, llm-training; Also covers Model Training; Need specialized support from Beijing Academy of Artificial Intelligence. ### When should I choose airllm over Aquila2? Choose airllm over Aquila2 when airllm is primarily Jupyter Notebook; Aquila2 is Python; Requirements: Min 4 GB RAM; Installation is straightforward via pip.; Tags unique to airllm: chinese-llm, chinese-nlp, finetune, generative-ai; When you need to perform inference on a 70B parameter model with limited GPU resources, such as a single 4GB GPU. ### When should I avoid Aquila2? Require comprehensive API and documentation clarity Preferring open source licensing details ### When should I avoid airllm? If your project requires inference on models larger than 70B parameters or if you have access to more powerful GPUs than a 4GB model. For projects that do not involve Chinese language models or generative AI tasks, as AirLLM is specifically optimized for these areas. ### Is Aquila2 or airllm more popular on GitHub? airllm has more GitHub stars (34,504 vs 445). Stars measure visibility, not whether either tool fits your constraints. ### Are Aquila2 and airllm open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to Aquila2 or airllm? GraphCanon lists graph-backed alternatives at [Aquila2 alternatives](/tools/flagai-open-aquila2/alternatives) and [airllm alternatives](/tools/lyogavin-airllm/alternatives) ([Aquila2 markdown twin](/tools/flagai-open-aquila2/alternatives.md), [airllm markdown twin](/tools/lyogavin-airllm/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-lyogavin-airllm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Aquila2 or airllm? Aquila2: Dormant. airllm: Very active. 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 airllm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Aquila2 trust report](/tools/flagai-open-aquila2/trust); [airllm trust report](/tools/lyogavin-airllm/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/_