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Datasets:
rtx-pro-4000
/
benchmarks

Tasks:
Text Generation
Modalities:
Tabular
Text
Formats:
json
Languages:
English
Size:
< 1K
Tags:
rtx-pro-4000
blackwell
llm-inference
owner-measured
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
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benchmarks / CONTRIBUTING.md
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Contributing Results

Benchmarks and configs are welcome. Support requests are out of scope.

Result Rules

  • Rows must be owner-measured on hardware the submitter operates.
  • Cloud, vendor, review-site, or copied rows are rejected.
  • variant is mandatory.
  • bandwidth_gbps, tdp_w, and pcie_lanes are mandatory and must match the declared desktop/SFF variant.
  • vram_gb, memory_type, and bus_width_bit are required metadata, but they do not identify desktop versus SFF. Desktop and SFF entries are both 24 GB GDDR7 ECC on a 192-bit bus.
  • Desktop, SFF, and laptop rows are accepted but segregated by variant and never merged into desktop tables.
  • Include enough metadata for another owner to repeat the run.
  • Tag related Hugging Face model cards with rtx-pro-4000.

Required Metadata

Use templates/result-row.json as the starting point.

Keep notes short but useful: backend flags, power method, whether the run was served or local, and what else was stopped to isolate the GPU.

Validation

Before submitting:

python validate.py data/results.jsonl

To validate a proposed row separately:

python validate.py path/to/proposed.jsonl

Rows with source other than owner-measured fail validation.