GPT-5.6 Luna is the stronger all-rounder.
Scores updated · 10 tests both models report · How we compare
Where each one wins
Tests won in each of the one area where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
What it costs
Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.
The biggest differences
The tests each model wins by the widest margin, up to three each. Scores are out of 100.
Where GPT-5.6 Luna pulls ahead
Where LFM3-Omni-2B pulls ahead
No clear win on a test scored out of 100.
Every test, side by side
All 10 tests both models report. The winning score is in its model's colour; marks a score checked independently.
Images and chartsGPT-5.6 Luna
Other results7 tests, not counted
Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.
- MMMU (val) (Pass@1)GPT-5.6 Luna by 32.875.242.4+32.8
- ERQAGPT-5.6 Luna by 1856.538.5+18
- MMBenchGPT-5.6 Luna by 10.784.473.7+10.7
- MV-BenchGPT-5.6 Luna by 10.268.258+10.2
- RealWorldQAGPT-5.6 Luna by 5.972.466.5+5.9
- POPELFM3-Omni-2B by 4.38589.3+4.3
- SEED-Bench (image)GPT-5.6 Luna by 1.176.275.1+1.1
Questions people ask
Which is better, GPT-5.6 Luna or LFM3-Omni-2B?
GPT-5.6 Luna wins the one area where both have results: images and charts. LFM3-Omni-2B wins none.
How do you compare the two?
We use the 10 benchmark tests both models have published scores on. The verdict counts the 3 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 7 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.