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OpenLedger enables deploying thousands of fine-tuned models using a single GPU without preloading them, by dynamically merging and infering on demand using quantization, flash attention, and tensor parallelism to offer 90% savings in deployment costs

July 2, 2025 //  by Finnovate

OpenLedger has launched OpenLoRA, a new open protocol that enables developers to deploy thousands of LoRA fine-tuned models using a single GPU, saving up to 90% of deployment costs. Built on cutting-edge research and an open-source foundation, OpenLoRA allows developers to serve thousands of LoRA models on one GPU without preloading them, dynamically merging and infering on demand using quantization, flash attention, and tensor parallelism. This means builders can now scale AI deployment without bloating compute bills. Deployed as a SaaS platform, OpenLoRA makes it radically easier for startups and enterprises alike to launch AI products across verticals, from marketing, legal, education, crypto, customer service, and beyond, without having to replicate the entire model architecture for each use case. It’s a paradigm shift in how fine-tuned intelligence can be deployed at scale. Ram, Core Contributor at OpenLedger said, “With OpenLoRA, we’re redefining the economics of AI deployment, offering the first protocol where developers can serve massive fleets of fine-tuned models with minimal cost and maximum performance.”

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