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@FooIbar FooIbar commented Dec 2, 2025

Fixes #2268

@jonnyawsom3
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It was previously attempted in #3368, but #3388 didn't work. Is a vckg triplet overlay not needed?

@FooIbar
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FooIbar commented Dec 10, 2025

Is a vckg triplet overlay not needed?

That is only used for building dependencies (libpng etc).

Benchmark results from https://github.com/libjxl/libjxl/actions/runs/19632494017/job/56215330523

31 images
Encoding                   kPixels    Bytes          BPP  E MP/s  D MP/s     Max norm  SSIMULACRA2   PSNR        pnorm       BPP*pnorm   QABPP   Bugs
-----------------------------------------------------------------------------------------------------------------------------------------------------
jpeg:yuv420:q85              13270  2917254    1.7586467 106.454 214.163   3.37124720  79.42429074  40.04   1.10613796  1.945305924119   5.817      0
webp:q80                     13270  1867908    1.1260556   3.067  40.377   3.32656463  74.40712702  39.34   1.24942530  1.406922414552   3.625      0
jxl:d1:6                     13270  2943410    1.7744147   1.594  20.149   1.33601265  86.79124710  42.11   0.58098713  1.030912109053   2.411      0
jxl:d1:6:downsampling=8      13270  2943410    1.7744147   1.603  30.884  35.05771513 -38.82501243  26.71  11.97750062 21.253053359670  62.559      0
jxl:d5:6                     13270   836542    0.5043037   1.630  12.613   4.56712682  59.55657986  34.48   1.84354865  0.929708333021   2.364      0
jxl:d5:6:downsampling=8      13270   836542    0.5043037   1.624  14.097  34.96340297 -40.00405983  26.66  11.94662018  6.024724280553  17.817      0
jxl:m:d0:2                   13270 18711007   11.2798034   9.728  16.902    -nan(ind) 100.00000000  99.99   0.00000000  0.000000000000  11.280      0
jxl:m:d0:3                   13270 17218229   10.3798923   4.833   6.085    -nan(ind) 100.00000000  99.99   0.00000000  0.000000000000  10.380      0
jxl:m:d2:2                   13270  4562929    2.7507307   7.080  11.829   2.79575955  77.13908798  36.76   1.15709056  3.182844561504   7.663      0
Aggregate:                   13270  3316683    1.9994400   4.485  21.911   5.85008903  55.38769561  43.84   2.19447850  2.708409555291   7.902      0

and https://github.com/FooIbar/libjxl/actions/runs/19863800403/job/56920760834

31 images
Encoding                   kPixels    Bytes          BPP  E MP/s  D MP/s     Max norm  SSIMULACRA2   PSNR        pnorm       BPP*pnorm   QABPP   Bugs
-----------------------------------------------------------------------------------------------------------------------------------------------------
jpeg:yuv420:q85              13270  2917254    1.7586467 105.013 217.396   3.37124720  79.42429074  40.04   1.10613796  1.945305923963   5.817      0
webp:q80                     13270  1867908    1.1260556   3.058  39.770   3.32656463  74.40712702  39.34   1.24942530  1.406922413676   3.625      0
jxl:d1:6                     13270  2943410    1.7744147   2.417  28.316   1.33601265  86.79199191  42.11   0.58098713  1.030912109936   2.411      0
jxl:d1:6:downsampling=8      13270  2943410    1.7744147   2.451  42.384  35.05771513 -38.82501243  26.71  11.97750063 21.253053377612  62.559      0
jxl:d5:6                     13270   836542    0.5043037   2.662  24.873   4.56712682  59.55566729  34.48   1.84354865  0.929708333687   2.364      0
jxl:d5:6:downsampling=8      13270   836542    0.5043037   2.662  27.524  34.96340297 -40.00405983  26.66  11.94662019  6.024724285257  17.817      0
jxl:m:d0:2                   13270 18711007   11.2798034  11.316  18.947    -nan(ind) 100.00000000  99.99   0.00000000  0.000000000000  11.280      0
jxl:m:d0:3                   13270 17218229   10.3798923   5.635   6.400    -nan(ind) 100.00000000  99.99   0.00000000  0.000000000000  10.380      0
jxl:m:d2:2                   13270  4562929    2.7507307   7.964  14.310   2.79575955  77.13908798  36.76   1.15709056  3.182844563509   7.663      0
Aggregate:                   13270  3316683    1.9994400   5.748  28.480   5.85008903  55.38767696  43.84   2.19447850  2.708409556500   7.902      0

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The official Windows builds are much slower than the static Clang builds

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