IFStruct
LFM3-1.7B 93.7% In use
Models generate JSON or YAML that must follow a requested schema and phrasing constraints, without constrained decoding. A response passes only if every structural constraint holds.
2,000 frozen test prompts. The makers say it saturates near 100% for frontier models and targets small models.
Made by Liquid AI Released Jun 2026 Following precise instructions All tasks public Last in a launch post Oct 2026
Last model added Oct 2026
- Level
- Everyday Most adults, without training
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Open-ended Free-form text, documents, designs or media judged as a whole.
2
Models scored in lab cards
2
Launch posts list it, from 1 lab
LFM3-1.7B leads with 93.7%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
- 1 LFM3-1.7B 93.7%
- 2 LFM2.5-2.6B 85.5%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | LFM3-1.7B | 93.7% | Oct 2026 | Model card | |
| 2 | LFM2.5-2.6B | 85.5% | Aug 2026 | Model card |
The best score passed 85% in Aug 2026
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Reported by the lab in its model card
Best so far
One lab put it in a launch post in the last six months
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| 27 Oct 2026 | LFM3-1.7B | 93.7 | IFStruct |
| 4 Aug 2026 | LFM2.5-2.6B | 85.5 | IFStruct |
More in Instructions and chat
- IFEval In use Models answer about 500 prompts containing verifiable instructions such as word limits or required keywords. Code checks each instruction for strict and loose accuracy.
Gemma 4 31B IT 98.9% - IFBench In use 58 new out-of-domain verifiable output constraints. Scored by programmatic constraint checks (strict or loose).
Nemotron-Cascade 2 30B-A3B 82.9% - MultiChallenge In use Multi-turn conversations testing instruction retention, inference memory, versioned editing and self-coherence. Graded by LLM judge with rubrics. GPT-6.1 Sol 82%
- Multi-IF In use Models follow verifiable instructions over three-turn conversations in eight languages, extending IFEval. Scored by instruction accuracy at each turn. LFM3-1.7B 89.1%
- AdvancedIF In use Models respond to over 1,600 prompts with complex, multi-turn, and system-level instructions. A judge model checks each response against expert-written rubrics.
MAI-Thinking-1 85% - NV Chat Benchmark In use Models answer chat prompts from an internal NVIDIA set. The Nemotron 3.5 Super VL card labels the score an LMArena v3 proxy. Nemotron 3.5 Super VL 52.7