instruction following benchmark
Agentic IF Index (Internal) Leaderboard
Agentic IF Index (Internal) is an internal benchmark that aggregates evaluations of instruction-following in agentic settings.
Updated Sep 5, 2026
Models1
Model coverage1
MetricScore
EvidenceB
Agentic IF Index (Internal) Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelME | Score57.80% | Percentile100.00% | Participants1 | EvidenceC | Evaluated |
Agentic IF Index (Internal) Highlights
The leading models and scores on this benchmark.
The Top AI Models for Agentic IF Index (Internal)
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis agentic if index (internal) AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01MEMeta
- Score
- 57.80%
- Price
- $1.3 input / $4.3 output per 1M tokens
- Speed
- Up to 8.44 tok/s via Meta Model API
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures Agentic IF Index (Internal), not total model capability
Selection summary
Best AI Models for Agentic IF Index (Internal)
Muse Spark 1.3 currently leads Agentic IF Index (Internal) with 57.80%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What is Agentic IF Index (Internal)?
What Agentic IF Index (Internal) measures and how its scores work.
Agentic IF Index (Internal) is Meta's internal benchmark for evaluating instruction-following.
It measures compliance with tool-use constraints, fine-grained rubrics, compound constraints, long policies, and instructions embedded in structured workflows, reported as a Score ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Agentic IF Index (Internal)
- Modality
- text
- Primary category
- instruction following
- 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 Agentic IF Index (Internal).
Which model scores highest on Agentic IF Index (Internal)?
Muse Spark 1.3 is currently ranked first with 57.80%.
What are the top three models on Agentic IF Index (Internal)?
The current leaders are Muse Spark 1.3 (57.80%).
Which Agentic IF Index (Internal) model has the lowest official input price?
Muse Spark 1.3 has the lowest matched official input price at $1.3 input / $4.3 output per 1M tokens.
Which models are fastest among Agentic IF Index (Internal) results?
The fastest matched records are Muse Spark 1.3 (8.44 tok/s via Meta Model API).
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.