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Decision brief
AirLLM is a notable framework designed specifically for running large language models on low-resource hardware, such as a single 4GB GPU.
Good fit when
- If you have limited hardware resources but need to perform inferences on large language models (like the 70B parameter model that AirLLM supports), use AirLLM.
- AirLLM is ideal if your project involves Chinese NLP or LLMs, as it stands out with support for models like `chinese-llm`.
Avoid when
- Avoid using AirLLM if you require models to run on higher-end GPUs or multiple GPU clusters, as its strength lies in low-resource efficiency.
- Do not use AirLLM if you are working primarily with non-Chinese language datasets and models, since support for other languages may be less optimized compared to competition.
- Pricing:
- freemium - Free and open-source under the Apache-2.0 license; however, infrastructure costs apply.
- Requirements:
- Min 16 GB RAM; A single 4GB GPU is sufficient for using this framework to run large language model inferences.
Observed Jul 11, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (5d since push)
- As of 3w
- Provenance
- Not a fork · Personal account
- As of 3w
- Security (OSV)
- 4 low (4 low)
- As of 1mo
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Install
git clone https://github.com/lyogavin/airllmHow it fits your stack(8)
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Evidence and technical details
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Overview
A framework for running large language model (LLM) inferences on low-resource hardware, specifically a 4GB GPU.
Capability facts
- Languages
- jupyter notebook
Source: github.language · Jul 28, 2026
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Compatibility
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README
1. Install package
First, install the airllm pip package.
pip install airllm
For agents
This page has a .md twin and JSON over the API.