LFM3-1.7B vs MAI-Thinking-1
MAI-Thinking-1 leads the LLM Stats Score 32.4 to 25.0.
Liquid AI · Microsoft · Updated for 2026
Which is better?
MAI-Thinking-1 leads the overall LLM Stats Score 32.4 to 25.0, ranking #132 overall.
In the 4 individual benchmarks reported for both models, MAI-Thinking-1 wins 3; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose LFM3-1.7B
- you want the most recent training data — it shipped Oct 2026
- you need open weights you can self-host or fine-tune
Choose MAI-Thinking-1
- overall performance matters — it scores 32.4 and ranks #132 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 4 exact shared results
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for LFM3-1.7B · 23 for MAI-Thinking-1
LFM3-1.7B outperforms in 1 benchmarks (IFBench), while MAI-Thinking-1 is better at 3 benchmarks (GPQA, LiveCodeBench v6, SWE-Bench Verified).
MAI-Thinking-1 shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
MAI-Thinking-1 has 998.3B more parameters than LFM3-1.7B, making it 57703.5% larger.
License
Usage and distribution terms
LFM3-1.7B is licensed under LFM Open License v1.0, while MAI-Thinking-1 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
LFM Open License v1.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
LFM3-1.7B was released on 2026-10-27, while MAI-Thinking-1 was released on 2026-06-02.
LFM3-1.7B is 5 months newer than MAI-Thinking-1.
Oct 27, 2026
1 weeks ago
4mo newerJun 2, 2026
5 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against LFM3-1.7B and MAI-Thinking-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about LFM3-1.7B vs MAI-Thinking-1.