multimodal benchmark
RealKIE-FCC
RealKIE-FCC is a key information extraction benchmark drawn from real enterprise documents (FCC filings), part of the RealKIE suite of five novel datasets for enterprise key information extraction. Models must convert documents to markdown and extract structured fields against a specified JSON schema. Nova 2 reports results on a human-verified version of the dataset.
Updated Aug 11, 2026
Models3
Model coverage3
MetricScore
EvidenceB
RealKIE-FCC Ranking
Higher score ranks better on this benchmark.
| 1 | AM Nova 2 ProAmazon | 67.0% | 100.0% | 3 | C | |
| 2 | AMNova 2 LiteAmazon | 62.1% | 50.0% | 3 | C | |
| 3 | AMNova 2 OmniAmazon | 59.8% | 0.0% | 3 | C |
RealKIE-FCC Score Distribution
A closer view of the leading scores on this benchmark.
RealKIE-FCC Highlights
The leading models and scores on this benchmark.
What is RealKIE-FCC?
What RealKIE-FCC measures and how its scores work.
RealKIE-FCC is a key information extraction benchmark drawn from real enterprise documents (FCC filings), part of the RealKIE suite of five novel datasets for enterprise key information extraction. Models must convert documents to markdown and extract structured fields against a specified JSON schema. Nova 2 reports results on a human-verified version of the dataset.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- RealKIE-FCC
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- realkie-fcc|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about RealKIE-FCC.
Which model scores highest on RealKIE-FCC?
Nova 2 Pro is currently ranked first with 67.0%.
What does RealKIE-FCC measure?
RealKIE-FCC is a key information extraction benchmark drawn from real enterprise documents (FCC filings), part of the RealKIE suite of five novel datasets for enterprise key information extraction. Models must convert documents to markdown and extract structured fields against a specified JSON schema. Nova 2 reports results on a human-verified version of the dataset.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
3 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.