DGX Spark's GB10 chip (Grace Blackwell, SM121, 128GB unified memory, aarch64) has ten recurring failure modes across launch, memory, thermals, bandwidth, and precision. Each is named G1–G10 so it can be checked by number — the numbering is load-bearing for tooling that runs these. Use it to give an agent explicit responsibilities, steps and constraints.
DGX Spark's GB10 chip has one 128GB unified memory (UMA) pool shared by CPU and GPU, and a sustained power ceiling well below its rated figure. Both break discrete-GPU assumptions: headroom isn't what nvidia-smi reports, and a run that starts fast will slow down mid-job with no. Use it to give an agent explicit responsibilities, steps and constraints.
Last verified: 2026-07-14 — refresh when CUDA, PyTorch, or Unsloth major versions change. Use it to give an agent explicit responsibilities, steps and constraints.
DGX Spark ships a GB10 Grace Blackwell chip: aarch64 CPU, SM121 GPU, 128GB unified memory, CUDA 13. This is a narrower and younger platform than a standard x86 CUDA 12 box, so package selection and ABI matching matter more than usual — the wheel ecosystem for aarch64 + CUDA 13 is. Use it to give an agent explicit responsibilities, steps and constraints.
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets. We are happy to receive feedback and contributions.
DGX Spark's GB10 chip (Grace Blackwell, SM121, 128GB unified memory, aarch64) has ten recurring failure modes across launch, memory, thermals, bandwidth, and precision. Each is named G1–G10 so it can be checked by number — the numbering is load-bearing for tooling that runs these. Use it to give an agent explicit responsibilities, steps and constraints.
DGX Spark's GB10 chip has one 128GB unified memory (UMA) pool shared by CPU and GPU, and a sustained power ceiling well below its rated figure. Both break discrete-GPU assumptions: headroom isn't what nvidia-smi reports, and a run that starts fast will slow down mid-job with no. Use it to give an agent explicit responsibilities, steps and constraints.
Last verified: 2026-07-14 — refresh when CUDA, PyTorch, or Unsloth major versions change. Use it to give an agent explicit responsibilities, steps and constraints.
DGX Spark ships a GB10 Grace Blackwell chip: aarch64 CPU, SM121 GPU, 128GB unified memory, CUDA 13. This is a narrower and younger platform than a standard x86 CUDA 12 box, so package selection and ABI matching matter more than usual — the wheel ecosystem for aarch64 + CUDA 13 is. Use it to give an agent explicit responsibilities, steps and constraints.
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets. We are happy to receive feedback and contributions.