When2Call D
AI benchmark · Decision Models
- Domains
- Decision Models
- Tier
- D why
- Snapshot
What is When2Call?
When2Call measures LLM tool-calling decision-making: whether to call a tool, ask a follow-up question, answer directly, or admit the question can't be answered with provided tools.
General capability mostly
“When2Call is a benchmark designed to evaluate tool-calling decision-making for large language models (LLMs), including when to generate a tool call, when to ask follow-up questions”
huggingface.co/datasets/nvidia/When2Call ↗
Lineage
Benchmarks this one is built on and built from: versions, subsets, extensions and the indexes that combine them.
Derived benchmarks
From Text to Voice extension
“Evaluates tool-calling ability of omni-modal voice agents on audio-converted versions of text tool-calling benchmarks (Confetti, When2Call) with speaker variation and noise.”
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.
- Not yet read on X.
- 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 When2Call 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, 2026-10-16 snapshot.