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@9rum 9rum commented Dec 19, 2025

Summary

This PR adds support for Qualcomm QCM6490, which has been discussed in issue #7356.

Fixes

Fixes #7356.

Test plan

The changes in this PR have been tested with the official Llama example.

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❌ 5 New Failures, 1 Unrelated Failure

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@meta-cla meta-cla bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Dec 19, 2025
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9rum commented Dec 19, 2025

@pytorchbot label "release notes: backends"

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pytorch-bot bot commented Dec 19, 2025

Didn't find following labels among repository labels: release notes: backends

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9rum commented Dec 19, 2025

@pytorchbot label "release notes: qualcomm"

@pytorch-bot pytorch-bot bot added the release notes: qualcomm Changes to the Qualcomm backend delegate label Dec 19, 2025
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Hi @shewu-quic @chenweng-quic @winskuo-quic @DannyYuyang-quic @haowhsu-quic if you take a look at this PR fixing #7356

source: fix typo
@9rum 9rum changed the title add support for Qualcomm QCS6490 add support for Qualcomm QCM6490 Dec 19, 2025
@9rum 9rum closed this Dec 19, 2025
@9rum 9rum deleted the feature/qcs6490 branch December 19, 2025 18:00
@9rum 9rum restored the feature/qcs6490 branch December 19, 2025 18:02
@9rum 9rum reopened this Dec 19, 2025
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Thank you for contributing! I wonder how you run llama on QCM6490? It seems like v68 and doesn't support block wise quantization, which means the accuracy won't be ideal

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9rum commented Dec 20, 2025

@cccclai Thank you for your kind reply.
We first quantize Llama 3.2 1B using SmoothQuant then run in 16a8w.
In such settings, the MMLU accuracy was 51.16%.

BTW, I see there is an enum value conflict: error: duplicate case value: 'QCM6490' and 'SM8350' both equal '35'.
This error was not found in the previous release where SM8350 was not supported.
However, simply setting SoC number to SM8350 does not cover QCM6490 since their VTCM sizes are different.
Should I remove QCM6490 and comment it out?

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Support qcs6490 v68 arch for QNN backend

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