Multi-IF
We show this table for reference; we do not rank on it.
Meta benchmark of instruction following over multi-turn conversations in eight languages.
Benchmark score on Multi-IF — October 29, 2026
We compile the Multi-IF rows from provider self-reports. LFM3-1.7B is the only currently displayable sourced row, at 89.10%. We do not use these results to rank models overall.
1 modelInstruction FollowingRefreshingDisplay onlyUpdated October 29, 2026
Benchmark score table (1 model)
| Rank | Model / configuration | Score | Parameters (B) | Open / closed |
|---|---|---|---|---|
| 1 | LFM3-1.7BLiquidAI | 89.10% | Not reported | Open |
How to read this leaderboard
Operator receipt: 1 sourced row is currently displayable on this page; the only currently displayable sourced row is LFM3-1.7B at 89.10%.
Honest limit: Only Liquid AI-run results are stored so far, from one launch table. Display-only and excluded from weighted ranking.
About Multi-IF
Year
2024
Tasks
Multi-turn, multilingual instructions
Format
Instruction accuracy
Difficulty
Keeping constraints across turns and languages
Liquid AI reports it for LFM3-1.7B (October 27, 2026) at temperature 0.6 and top_p 0.95.
Freshness and provenance
Version
Multi-IF 2024
Refresh cadence
Annual
Staleness state
Refreshing
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
Questions
What does Multi-IF measure?
Meta benchmark of instruction following over multi-turn conversations in eight languages.
Which model scores highest on Multi-IF?
LFM3-1.7B by LiquidAI currently leads with a score of 89.10% on Multi-IF.
How many models are evaluated on Multi-IF?
1 AI models have published results on Multi-IF in the BenchLM catalog.
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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