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NVIDIA expands DGX Spark clusters to eight nodes for local AI

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NVIDIA expands DGX Spark clusters to eight nodes for local AI

NVIDIA says DGX Spark now supports eight-node clusters, lifting unified memory to 1TB and improving throughput for local AI workloads.

NVIDIA said it will officially support eight-node DGX Spark clusters, extending the desktop AI system from a four-node ceiling to configurations with 1TB of unified memory and higher throughput for inference, orchestration and small-model training. The company made the announcement at GTC Berlin in a blog post published Oct. 22, 2026, and said support in NVIDIA Sync is due by the end of the year.

According to NVIDIA, a single DGX Spark provides 128GB of unified memory, four nodes reach 512GB, and eight nodes reach 1TB. The company said that capacity lets developers load frontier-class models that would not fit on smaller configurations, including the full GLM 5.3 model from Z.ai, which NVIDIA described as a 753B parameter system. In an example test, NVIDIA said GLM 5.3 Flash ran across eight nodes at roughly 80 tokens per second, which it characterized as suitable for interactive local development.

3 checkpoint runs across the eight-node cluster in NVFP4 format, with the model measuring about 470GB in that precision. In the company’s table, prefill throughput for the full model was reported at 1,600 TPS at one, four and eight concurrent users, while decode throughput rose from 31 TPS at one user to 67 TPS at eight users. Those figures were presented by NVIDIA in the Oct. 22 post and reflect the company’s benchmark setup, including 8K input sequence length for prefill.



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