Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for developers shipping schema-guided extraction APIs, enterprises evaluating vendor extraction claims, and researchers comparing extraction model paths.
Who should use it
Who should skip it
Consider run-llama/ExtractBench lower priority if you already have a working solution in this category.
About this signal
run-llama/ExtractBench is tracked by RepoRadar as a developer tool in the Evaluation Benchmark section. First seen 2026-08-12; the source record was last checked on 2026-08-12. The current verdict is 'try now' with a Silver tier and easy setup difficulty. Across RepoRadar's eight signals, run-llama/ExtractBench is strongest on novelty (10.0) and workflow potential (8.9) and weakest on maturity (5.7) — a profile worth weighing against your own priorities. This page summarizes the public evidence on the linked source page and states where additional review is still needed.
How this item is evaluated
The run-llama/ExtractBench record combines a 7.8/10 composite score with separate popularity (0.3), risk (low), and setup (easy) signals. See the scoring methodology for the current weights and evidence definitions.
Putting this into practice? Read How to read AI benchmarks without getting fooled for the checklist behind this score.
Risk explanation
It ships its own datasets and a leaderboard; review the dataset license before reusing the datasets in a commercial benchmark; It depends on the LlamaIndex extraction pipeline; track library updates and pin to a known-good version when adopting as a default.