MoE-Infinity
PyTorch library for cost-effective, fast and easy serving of MoE models.
Run large AI models efficiently on devices with limited memory by managing data transfer intelligently.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimePyTorch library for cost-effective, fast and easy serving of MoE models.
MoE-Infinity has 352 stars on GitHub. It has been forked 38 times. MoE-Infinity is written mainly in Python. It has been in active development since 2024. MoE-Infinity is available under the Apache-2.0 license. Its main topics are huggingface, inference-engine, large-language-models, llm-inference.
What is MoE-Infinity?
PyTorch library for cost-effective, fast and easy serving of MoE models.
Is MoE-Infinity open source?
MoE-Infinity is an open-source project. It is released under the Apache-2.0 license.
Is MoE-Infinity free?
Yes. MoE-Infinity is free and open source — you can use, modify and self-host it.
What license does MoE-Infinity use?
MoE-Infinity is available under the Apache-2.0 license.
What language is MoE-Infinity written in?
MoE-Infinity is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/efficientmoe-moe-infinity.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.