Demux sequence summary length much smaller than actual sequences are/should be

Hi all!
My problem is similar to this topic, however I have follow up questions I can't post in that topic:
Demultiplexed sequence length summary identical forward and reverse for emp paired end reads - User Support - QIIME 2 Forum

So I've played around with Qiime2 for a little bit, but I'm still very new to doing anything with sequence data.
I'm running q2 2021.11 on VM virtualbox on my laptop.
To the problem:
I have paired-end demultiplexed sequences from illumina sequencing run, where 27F and 519R 16S rDNA primers were used. I used the code from importing data Casava 1.8 paired-end demultiplexed fastq. I get my demux.qza file and I do the summary, where I see this:


and

Why are my sequences suddenly only 301nts? I'm expecting them to be a bit longer, atleast in the 400-s. Is this what happens during importing and generating the demux file?
(I also run into an issue at taxonomy stage, where I have very large portion of unassigned, which makes me come back to the very beginning and thinking this might be one of the issues..)

I also used Mothur through Galaxy.org to see if there are slight differences, and where I combine the forward and reverse reads I get a summary like this:
Start End NBases Ambigs Polymer NumSeqs
Minimum:1 293 293 0 3 1
2.5%-tile: 1 391 391 0 4 248117
25%-tile: 1 490 490 0 5 2481164
Median: 1 498 498 0 5 4962328
75%-tile: 1 514 514 0 5 7443491
97.5%-tile:1 588 588 13 18 9676538
Maximum:1 602 602 157 300 9924654
Mean: 1 501.061 501.061 1.18359 6.20446

of Seqs: 9924654

So, the number of sequences is the same. However, the length is what worries me.
If I now go on with the 301 truncation in dada2, I would lose a considerable amount of data in my mind.
The denoising I would run next:
qiime dada2 denoise-paired
--i-demultiplexed-seqs demux.qza
--p-trim-left-f 6
--p-trim-left-r 6
--p-trunc-len-f 301
--p-trunc-len-r 301
--o-table table.qza
--o-representative-sequences rep-seqs.qza
--o-denoising-stats denoising-stats.qza

Should I worry about the 301nt length? I understand the quality score interactive blot is a subsample of all of my samples, but shouldn't some of my reads at least go past 301? Perhaps the original data is at fault?
I'm still learning and trying to find different solutions to the problems I encounter using Q2, but this is something I can't seem to figure out.
Cheers,
El