forum threadSuryasis posted Nov 29, 2025 05:31 AM
Item 1 of 4
Item 1 of 4
forum threadSuryasis posted Nov 29, 2025 05:31 AM
HP Z2 Mini G1a AI Workstation: Ryzen AI MAX+ Pro 395, 128GB LPDDR5X, 2TB Gen4 SSD, 2xTB4, Wi-Fi7, Win11P, 3Yrs Onsite Warranty @ $2249.10 + F/S
$2,249
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And then get a 512gb ssd (+$20) and this is down to less than 1800 for the 395max
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NVIDIA DGX Spark
Best for: Training, fine-tuning, and inference with models specifically optimized for its unique NVFP4 format.
Strengths: 128GB of unified memory, compact form factor, and designed for a complete AI sandbox experience.
Weaknesses: Slower inference speeds compared to high-end GPUs for standard models, with benchmarks showing it being slower than a 5090 and significantly slower than a Pro 6000. The memory bandwidth is a bottleneck for large batch sizes
yeah fam the whole Internet is wrong and you're right. again that box is not for inference. It's for development two different things.
NVIDIA DGX Spark
Best for: Training, fine-tuning, and inference with models specifically optimized for its unique NVFP4 format.
Strengths: 128GB of unified memory, compact form factor, and designed for a complete AI sandbox experience.
Weaknesses: Slower inference speeds compared to high-end GPUs for standard models, with benchmarks showing it being slower than a 5090 and significantly slower than a Pro 6000. The memory bandwidth is a bottleneck for large batch sizes
yeah fam the whole Internet is wrong and you're right. again that box is not for inference. It's for development two different things.
NVIDIA DGX Spark
Best for: Training, fine-tuning, and inference with models specifically optimized for its unique NVFP4 format.
Strengths: 128GB of unified memory, compact form factor, and designed for a complete AI sandbox experience.
Weaknesses: Slower inference speeds compared to high-end GPUs for standard models, with benchmarks showing it being slower than a 5090 and significantly slower than a Pro 6000. The memory bandwidth is a bottleneck for large batch sizes
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