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docs(ocrbench): the one-batch image decode is a per-host fact, not the build - #330

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Sep 19, 2026
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The last piece of #326 that #327 did not already absorb.

The CUDA ladder's config table says:

| engine | the deployed build 0.34.1-dynres-16-g16649e8 | GGUF arms therefore decode the image in one batch (ADR 0036) |

True on that discrete card. False on gfx1151, where ADR 0036's own diagnostic fires on every gemma4 load:

msg="generation batch below the image chunk, images decode in pieces" num_batch=1024 image_chunk_batch=2048

The 2048 floor is refused at every quantisation — 1024 for q4 at -np 1, 512 for q8 and bf16 — because availableMemoryForLoad takes its integrated-GPU branch and sizes the batch against 31 GiB of system RAM while the scheduler logs available="95.4 GiB" of GPU. On a discrete card that branch never triggers.

As written the row invites the next reader to infer a decode path from a build stamp regardless of host. Now qualified, and pointing at the ROCm doc that carries the measurement.

🤖 Generated with Claude Code

…e build

"GGUF arms therefore decode the image in one batch (ADR 0036)" holds on
the discrete CUDA card the CUDA ladder was measured on. It does not hold
on gfx1151, where ADR 0036's own diagnostic fires on every gemma4 load
and the 2048 floor is refused at every quantisation -- because
availableMemoryForLoad takes its integrated-GPU branch and sizes the
batch against 31 GiB of system RAM while the scheduler logs 95.4 GiB of
GPU free.

Left as-is the row invites the next reader to infer a decode path from a
build stamp on whatever host they are on. Points at the ROCm doc, which
carries the measurement and the arithmetic; ADR 0036 already records it.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
@glennneuber
glennneuber merged commit 1b68c50 into main Sep 19, 2026
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glennneuber deleted the docs/ocrbench-engine-row-per-host branch September 19, 2026 08:16
glennneuber pushed a commit that referenced this pull request Sep 19, 2026
#330 landed the same correction with the root cause named — availableMemoryForLoad
takes its integrated-GPU branch on gfx1151 and sizes the batch against 31 GiB of
system RAM while the scheduler logs 95.4 GiB of GPU. That is the better text.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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