M5 Ultra 256GB or 2x DGX Spark? Which one?

Reddit r/LocalLLaMA News

Summary

A community post weighing whether to buy an M5 Ultra 256GB or dual NVIDIA DGX Spark units for local LLM inference and agentic coding, comparing prompt processing and throughput trade-offs against an existing RTX 5090 setup.

Currently contemplating adding either M5 Ultra 256GB or dual DGX Spark in addition to existing 5090. I have been researching for past few days and have zeroed in on dual sparks because higher throughput for agentic coding / multiple parallel requests and prompt processing advantage over M5 ultra. Since the local LLM landscape changes everyday, it is difficult to find metrics generated by the same author. Ref: Mindstudio article comparing two. So far from what I have read, token generation is close match or slightly better with M5 ultra, whereas sparks take lead in prompt processing and multiple users/parallel requests. I am well aware that I will see 1/3rd of 5090 tokens speed with this choice but I will be able to run larger models. I am just not confident about the final choice for agentic coding - M5 Ultra 256GB or dual DGX Sparks? If you own either of these, can you please share the model you use, overall experience and basic metrics such as prompt processing and decode speeds? Thank you!
Original Article

Similar Articles

M5 vs DGX Spark vs Strix Halo vs RTX 6000

Reddit r/LocalLLaMA

A user benchmarked M5 Macs, DGX Spark, Strix Halo, and RTX 6000 on AI workloads over 3 days, publishing results to GitHub. The M5 outperforms DGX Spark in memory bandwidth and token generation, while the MacBook's thermals were surprisingly good but noisy.

Got 2x DGX Sparks. Excited and confused!

Reddit r/LocalLLaMA

一位用户分享了购买两台 Nvidia DGX Spark(约6100美元/台)的经历,用于学习和编程工作流,并询问 GLM 5.3 flash 的本地部署配方以及 Nvidia 论坛是否是获取相关资讯的最佳渠道。