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Add MTP support for hybrid models#2363

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deepakn94 merged 55 commits intoNVIDIA:mainfrom
rkarimimahab:rkarimimahab/mtp
Feb 1, 2026
Merged

Add MTP support for hybrid models#2363
deepakn94 merged 55 commits intoNVIDIA:mainfrom
rkarimimahab:rkarimimahab/mtp

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@rkarimimahab
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@rkarimimahab rkarimimahab commented Nov 23, 2025

What does this PR do ?

(1) supporting to use hybrid mamba models as mtp_model_layer.
(2) splitting the MTP loss calculation in the GPT model’s forward pass into a separate function.
(3) supporting MTP layer repetition.

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@rkarimimahab rkarimimahab requested review from a team as code owners November 23, 2025 11:30
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@shifangx
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shifangx commented Dec 8, 2025

This pr implements three features:
(1) supporting to use Mamba layer as mtp_model_layer.
(2) splitting the MTP loss calculation in the GPT model’s forward pass into a separate function.
(3) supporting MTP layer repetition.
I have no concerns about the implementation of the first two features.
As for the last feature, we need to consider how to support scenarios where multiple MTP layers are placed on different PP ranks for computation. These MTP layers share the same parameters value, but be placed onto different vpp stage, in order to make sure each vpp stage do not have much computation task.
Maybe we can use assert to guide users can not place mtp layers into different vpp stage currently, and support this feature in future.

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This pr implements three features: (1) supporting to use Mamba layer as mtp_model_layer. (2) splitting the MTP loss calculation in the GPT model’s forward pass into a separate function. (3) supporting MTP layer repetition. I have no concerns about the implementation of the first two features. As for the last feature, we need to consider how to support scenarios where multiple MTP layers are placed on different PP ranks for computation. These MTP layers share the same parameters value, but be placed onto different vpp stage, in order to make sure each vpp stage do not have much computation task. Maybe we can use assert to guide users can not place mtp layers into different vpp stage currently, and support this feature in future.

This is a good point. Let's go with the assertion for now re: 3.

@rkarimimahab
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rkarimimahab commented Dec 9, 2025

This is a good point. Let's go with the assertion for now re: 3.

I added the assert, thanks!

@rkarimimahab rkarimimahab requested review from a team as code owners December 18, 2025 17:57
@deepakn94 deepakn94 self-requested a review December 21, 2025 05:50
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sancha commented Feb 1, 2026

/ok to test 9cc1668

@deepakn94 deepakn94 added this pull request to the merge queue Feb 1, 2026
Merged via the queue into NVIDIA:main with commit 300d1b6 Feb 1, 2026
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arendu pushed a commit to arendu/Megatron-LM that referenced this pull request Feb 5, 2026
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For posterity, this PR was re-merged as #3207 with some bugfixes.

arendu added a commit to arendu/Megatron-LM that referenced this pull request Feb 18, 2026
Signed-off-by: adithyare <adithyare@nvidia.com>
arendu added a commit to arendu/Megatron-LM that referenced this pull request Feb 21, 2026
Signed-off-by: adithyare <adithyare@nvidia.com>
yfw pushed a commit to yaoyu-33/Megatron-LM that referenced this pull request Feb 23, 2026
daiyaanarfeen pushed a commit to daiyaanarfeen/Megatron-LM that referenced this pull request Feb 23, 2026
Co-authored-by: Rabeeh Mahabadi <rkarimimahab@nb-hel-cs-001-vscode-02.cm.cluster>
Co-authored-by: Sanjeev Satheesh <sasatheesh@nvidia.com>
Co-authored-by: Deepak Narayanan <dnarayanan@nvidia.com>
daiyaanarfeen pushed a commit to daiyaanarfeen/Megatron-LM that referenced this pull request Feb 23, 2026
daiyaanarfeen pushed a commit to daiyaanarfeen/Megatron-LM that referenced this pull request Feb 23, 2026
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