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Is LFM3-Omni-2B worse or roughly equal at vision tasks compared to LFM3-VL-2B?

In other words: Should I select the model that matches my desired capability set or just use Omni?

unfortunately the models are still stronger without extra modalities. So LFM3-1.7B is better at pure text tasks than all other models. the LFM3-VL-2B is better at text/vision tasks than the Omni, the Audio model is a stronger ASR/TTS model than the Omni, etc.

It's a goal of ours to continue unifying training across modalities so that there is truly one model, instead of just this shared pre-trained backbone.

Is it a parameter count problem? Ie why are you not seeing the cross modality bump in performance?

Has the cross modaility bump been conclusively proven?

my intuition is that cross modality improvements do not really show up in practice, and especially not in small models

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