{"id":54838,"date":"2026-05-02T07:48:00","date_gmt":"2026-05-02T00:48:00","guid":{"rendered":"https:\/\/thaipropertynews.com\/feeds\/?p=54838"},"modified":"2026-05-02T07:48:00","modified_gmt":"2026-05-02T00:48:00","slug":"moreh-demonstrates-production-ready-llm-inference-on-tenstorrent-galaxy-achieving-dgx-a100-class-performance-with-improved-cost-efficiency","status":"publish","type":"post","link":"https:\/\/thaipropertynews.com\/feeds\/?p=54838","title":{"rendered":"MOREH Demonstrates Production-Ready LLM Inference on Tenstorrent Galaxy, Achieving DGX A100-Class Performance with Improved Cost Efficiency"},"content":{"rendered":"

R<\/span>educes HBM Costs with GPU\u2013Tenstorrent Heterogeneous Distributed Serving
<\/span><\/i><\/b>First unveiled at Tenstorrent’s launch event, TT-Deploy, in San Francisco on May 1<\/span><\/i><\/b><\/p>\n

SANTA CLARA, Calif.<\/span>, May 2, 2026 \/PRNewswire\/ — Moreh<\/a>, an AI infrastructure software company, led by CEO Gangwon Jo, announced that it has successfully validated LLM inference performance on the Tenstorrent Galaxy Wormhole system using its proprietary ‘MoAI Inference Framework.’<\/span><\/p>\n

\n

\"\" <\/a>
<\/span><\/p>\n<\/div>\n

Based on tests across leading Mixture-of-Experts (MoE) models\u2014including GPT-OSS, Qwen, GLM, and DeepSeek\u2014Moreh achieved LLM inference performance on Tenstorrent Galaxy Wormhole matching or surpassing NVIDIA DGX A100-class systems, demonstrating a compelling alternative to conventional GPU-centric AI infrastructure.<\/p>\n

Moreh also improved cost efficiency by implementing a disaggregated serving architecture that combines GPUs with Tenstorrent Wormhole chips. By utilizing Tenstorrent processors as dedicated prefill accelerators, the company reduced reliance on high-cost HBM and lowered overall infrastructure costs.<\/p>\n

The results were first unveiled at Tenstorrent’s launch event, TT-Deploy, held on May 1 in San Francisco.<\/p>\n

As a strategic partner of Tenstorrent and a major external contributor to Metalium, Moreh showcased a live LLM inference demo at the event. Building on its experience operating AMD GPU-based production environments in real-world data centers, the company presented its latest technical achievements in ‘Production-Ready LLM Inference on Tenstorrent Galaxy.’<\/p>\n

MoAI Inference Framework is a disaggregated inference solution that enables unified operation of heterogeneous GPUs and NPUs\u2014including NVIDIA, AMD, and Tenstorrent\u2014within a single cluster. This allows enterprises to build flexible AI infrastructure strategies without vendor lock-in.<\/p>\n

Moreh CEO Gangwon Jo stated, “Achieving production-grade LLM inference performance and stability on Tenstorrent-based systems marks a significant milestone,” and added, “We will continue to enhance performance through deeper optimization across heterogeneous architectures and closer integration with Tenstorrent NPUs.”<\/p>\n

Moreh is developing its own core AI infrastructure engine and, through its foundation LLM subsidiary Motif Technologies, is building end-to-end capabilities spanning both infrastructure and model domains. Simultaneously, the company is making its mark in the global market through collaborations with key partners such as AMD, Tenstorrent, and SGLang.<\/p>","protected":false},"excerpt":{"rendered":"

<\/p>\n

R<\/span>educes HBM Costs with GPU\u2013Tenstorrent Heterogeneous Distributed Serving
<\/span><\/i><\/b>First unveiled at Tenstorrent’s launch event, TT-Deploy, in San Francisco on May 1<\/span><\/i><\/b><\/p>\n

SANTA CLARA, Calif.<\/span>, May 2, 2026 \/PRNewswire\/ — Moreh<\/a>, an AI infrastructure software company, led by CEO Gangwon Jo, announced that it has successfully validated LLM inference performance on the Tenstorrent Galaxy Wormhole system using its proprietary ‘MoAI Inference Framework.’<\/span><\/p>\n

\n

\"\" <\/a>
<\/span><\/p>\n<\/div>\n

Based on tests across leading Mixture-of-Experts (MoE) models\u2014including GPT-OSS, Qwen, GLM, and DeepSeek\u2014Moreh achieved LLM inference performance on Tenstorrent Galaxy Wormhole matching or surpassing NVIDIA DGX A100-class systems, demonstrating a compelling alternative to conventional GPU-centric AI infrastructure.<\/p>\n

Moreh also improved cost efficiency by implementing a disaggregated serving architecture that combines GPUs with Tenstorrent Wormhole chips. By utilizing Tenstorrent processors as dedicated prefill accelerators, the company reduced reliance on high-cost HBM and lowered overall infrastructure costs.<\/p>\n

The results were first unveiled at Tenstorrent’s launch event, TT-Deploy, held on May 1 in San Francisco.<\/p>\n

As a strategic partner of Tenstorrent and a major external contributor to Metalium, Moreh showcased a live LLM inference demo at the event. Building on its experience operating AMD GPU-based production environments in real-world data centers, the company presented its latest technical achievements in ‘Production-Ready LLM Inference on Tenstorrent Galaxy.’<\/p>\n

MoAI Inference Framework is a disaggregated inference solution that enables unified operation of heterogeneous GPUs and NPUs\u2014including NVIDIA, AMD, and Tenstorrent\u2014within a single cluster. This allows enterprises to build flexible AI infrastructure strategies without vendor lock-in.<\/p>\n

Moreh CEO Gangwon Jo stated, “Achieving production-grade LLM inference performance and stability on Tenstorrent-based systems marks a significant milestone,” and added, “We will continue to enhance performance through deeper optimization across heterogeneous architectures and closer integration with Tenstorrent NPUs.”<\/p>\n

Moreh is developing its own core AI infrastructure engine and, through its foundation LLM subsidiary Motif Technologies, is building end-to-end capabilities spanning both infrastructure and model domains. Simultaneously, the company is making its mark in the global market through collaborations with key partners such as AMD, Tenstorrent, and SGLang.<\/p>\n

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