GDP.pdf w/ Python D
AI benchmark · Multimodal
- Domains
- Multimodal
- Tier
- D why
- Snapshot
What is GDP.pdf w/ Python?
GDP.pdf w/ Python measures professional document understanding, where the model receives each original PDF in a sandbox and uses an IPython tool, graded by rubric pass rate.
Enterprise work mostly
“For GDP.pdf w/ python: Each original PDF file is sent to the sandbox, where the model can use IPython tool to process it.”
alphaxiv.org/abs/2610.kimi-k3-1-pro ↗
Lineage
Benchmarks this one is built on and built from: versions, subsets, extensions and the indexes that combine them.
Built on
GDP.pdf original
Tier D
Long tail: little or no usage data yet.
How much stands behind a tier: usage, who backs it, a confirmed line from its own site or paper, and a clear read on X. High with three of the four, medium with two, low otherwise.
- no usage data
- in curated RL directories (1 pt)
How we got to tier D
- Adoption: no usage data. Tier D.
- On X: unclear, none buzz No move.
- In curated RL directories: 1 point, a floor of none.
- Confirmed: a line from its own site or paper places it.
A clear view on X moves a tier one step up or down; most entries don't move. How tiers work.
Where GDP.pdf w/ Python sits
Its domain on the map, live. Hover a logo for its name; click to open it. Open it on the full map
Next: browse all benchmarks. Entry from the RL Research daily scrape of public sources, 2026-10-29 snapshot.