NVIDIA’s GB200 NVL72 and Dynamo improve MoE model performance

According to the NVIDIA’s recent report, NVIDIA continues to promote AI performance with the latest GB200 NVL72 and NVIDIA Dynamo, which greatly improves the inference performance of the MOE model according to the recent report of NVIDIA. This development promises to be a game chain of AI distribution by optimizing calculation efficiency and reducing costs.

The power of the MOE model

The latest waves of the latest open source large language models (LLMS) such as DeepSeek R1, LLAMA 4 and QWEN3 have adopted the MOE architecture. Unlike traditional models, the MOE model activates only the sub -set of special parameters or “experts” during reasoning, reducing the operation time and reducing operating costs. NVIDIA’s GB200 NVL72 and Dynamo use this architecture to unlock new levels of efficiency.

Separated serving and model parallel treatment

One of the main innovations discussed is separate serving, which allows independent optimization by separating the pre -fill and decoding phase of other GPUs. This approach improves efficiency by applying a variety of model parallel treatment strategies that meet the specific requirements of each stage. Expert parallel processing (EP) is introduced in a new dimension to distribute model experts to GPUs to improve resource utilization.

The role of optimization of nvidia dynamo

NVIDIA Dynamo, a distributed reasoning serving framework, simplifies the complexity of the separated serving architecture. In order to optimize the calculation with the GPU and intelligently, we manage the quick transmission of KV cache between the path. Dynamo’s dynamic speed matching is effectively assigned to prevent idle GPUs and optimize throughput.

NVIDIA GB200 NVL72 NVLINK Architecture

The NVLINK architecture of the GB200 NVL72 supports up to 72 NVIDIA BLACKWELL GPUs, providing 36 times faster than the current Ethernet standard. This infrastructure is important for the MOE model that requires all high -speed communication between experts. The function of the GB200 NVL72 is an ideal choice to provide services to the MOE model with a wide range of professional parallel processing.

Beyond Moe: Accelerates a dense model

In addition to the MOE model, NVIDIA’s innovation improves the performance of traditional dense models. The GB200 NVL72, which is paired with Dynamo, shows significant performance gains for models such as LLAMA 70B, adapting to larger waiting time constraints and increasing throughput.

conclusion

NVIDIA’s GB200 NVL72 and DYNAMO show a significant leap of AI reasoning efficiency, allowing AI factories to maximize GPU usage and provide more requests per investment. This development is a pivotal stage that optimizes AI deployment and leads continuous growth and efficiency.

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