December 26, 2025
SLOPE Engine improves long-context prefill performance by applying context parallelism across multiple GPU servers. This also helps efficiently utilize older-generation GPUs.
November 10, 2025
TIDE provides a method to optimize inference computation on newer GPUs by utilizing older or idle GPUs for runtime draft model training, resulting in better overall cost-performance at the system level.
September 23, 2025
MoAI Inference Framework supports automatic and efficient distributed inference on heterogeneous accelerators such as AMD MI300X + MI308X and NVIDIA Rubin CPX + GPU.
February 20, 2025
MoAI provides a PyTorch-compatible environment that makes LLM fine-tuning on hundreds of AMD GPUs super easy, including DeepSeek 671B MoE.
December 2, 2024
Moreh announces the release of Motif, a high-performance 102B Korean language model (LLM), which will be made available as an open-source model.
September 3, 2024
There are no barriers to fine-tune Llama 3.1 405B on the MoAI platform. The Moreh team has actually demonstrated fine-tuning on the model with 192 AMD GPUs.
August 19, 2024
The MoAI platform provides comprehensive GPU virtualization including fine-grained resource allocation, multi-GPU scaling, and heterogeneous GPU support.
August 14, 2023
Moreh trained a largest-ever Korean LLM with 221B parameters on top of the MoAI platform and an 1,200 AMD MI250 cluster system.
November 11, 2022
KT has collaborated with Moreh and AMD to overcome the challenges in public cloud services and in-house AI model development.
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