long context benchmark
SummScreenFD Leaderboard
SummScreenFD is the ForeverDreaming subset of the SummScreen dataset, containing TV series transcripts paired with human-written recaps from 88 different shows for abstractive screenplay summarization.
Updated Sep 5, 2026
Models2
Model coverage2
MetricScore
EvidenceB
SummScreenFD Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelMI | Score16.90% | Percentile100.00% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelMI | Score16.00% | Percentile0.00% | Participants2 | EvidenceC | Evaluated |
SummScreenFD Highlights
The leading models and scores on this benchmark.
SummScreenFD Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for SummScreenFD
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What is SummScreenFD?
What SummScreenFD measures and how its scores work.
A long-context benchmark based on TV series transcripts and human-written recaps from 88 different shows.
It reports a Score metric as a ratio for abstractive screenplay summarization.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- SummScreenFD
- Modality
- text
- Primary category
- long context
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- overall
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about SummScreenFD.
Which model scores highest on SummScreenFD?
Phi-3.5-MoE-instruct is currently ranked first with 16.90%.
What are the top three models on SummScreenFD?
The current leaders are Phi-3.5-MoE-instruct (16.90%) and Phi-3.5-mini-instruct (16.00%).
Which SummScreenFD model has the lowest official input price?
No matched official input price is currently available.
Which models are fastest among SummScreenFD results?
The fastest matched records are Phi-3.5-mini-instruct (23.00 tok/s via Azure).
Does the highest score result prove overall model quality?
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.