bugfix: update xllm_ops submodule for dynamic mega chunk gdn heads.

[Sinle4Cat]

Description

Update the third_party/xllm_ops submodule to the latest xLLM-AI/xllm_ops main commit.

• Included fix: dynamic mega_chunk_gdn synchronization update from xllm_ops.

This PR only changes the xllm_ops submodule gitlink. No xLLM source code is modified.

Related Issues

N/A

Change Type

• Bug fix
• New feature
• Performance improvement
• Refactor
• Documentation
• Test
• Build or CI

Pull Request Checklist

Thank you for contributing to xLLM. Before requesting review, please make sure the following items are complete.

PR Title and Commit Messages

• The PR title and each commit message follow the xLLM commit format: <type>: <subject>.

Allowed types: feat, bugfix, docs, test, refactor, chore, style, revert, perf, model, build, release.
The subject should use clear English, start with a verb, include at least 4 words, and end with ..

Pre-commit Checks

• I have installed pre-commit by running pip install pre-commit or an equivalent command.
• I have installed the hooks with pre-commit install.
• I have run pre-commit run --all-files and fixed any reported issues.

If you are unsure how to set up pre-commit, see the pre-commit documentation.

Self Review

• I have self-reviewed the code according to .agents/skills/code-review/references/custom-code-style.md, especially code written or assisted by AI.
• I have rebased this PR onto the latest main branch.

Build and Test Coverage

• Tests have been added or updated as needed.
• CUDA: python setup.py build test has passed on a CUDA machine.
• NPU: python setup.py build test has passed on an NPU machine.
• MLU: python setup.py build test has passed on an MLU machine.

Reviewer Notes

• This PR is a submodule pointer update only.
• The target xllm_ops commit is the current xLLM-AI/xllm_ops main head: 7345ef6027167a6efd739370bee0a66a4c31ad6d.
• xllm_ops verification on npu:
  • mega_chunk_gdn build passed.
  • test_mega_chunk_gdn.py: 28 passed.
  • Full xllm_ops custom ops build passed.
  • Python test files passed when run in isolated pytest processes; one single-process full pytest run had a transient order-
• Qwen3.6-35B TP 1,2,4,8 benchmark passed on continuous NPU devices
• Qwen3.6-35B no-MTP/MTP ceval dataset accuracy 91.68.
• multimodal qwen3-5-27b TP 4：tested in textvqa accuracy gen 83.23

[yingxudeng]

LGTM