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Daniel Korzekwa fadbf74d31 Make the QAT/QAD guide the central place for concepts, background, and framework selection (#2590) 
### What does this PR do?

Make the QAT/QAD guide the central place for concepts, background, and
framework selection. Have the Hugging Face and Megatron Bridge tutorials
link back to it instead of repeating explanations of QAT and QAD,
keeping the tutorials focused on setup and execution. In main QAT/QAD
guide make links to all relevant blogposts.

Note: MBridge example doc is out of scope for this MR.

### Testing
Doc changes only, manual check.

### Before your PR is "*Ready for review*"
- Is this change backward compatible?: ✅ 
- Did you write any new necessary tests?: N/A docs changes only

### Additional Information
<!-- E.g. related issue. -->


<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

* **Documentation**
* Expanded the QAT/QAD guide with workflows, use cases, and a
comparison, including QAD’s use of a frozen BF16 teacher and logit-level
loss to recover accuracy after quantization.
* Updated README and quick-start navigation to link to the combined
QAT/QAD guide; the previous standalone QAT guide now redirects readers
there.
* Reorganized the LLM QAT tutorial: recipe guidance is now part of the
end-to-end example, while trainer examples and Python
quantize-and-fine-tune guidance are in Advanced Topics. The tutorial
also notes Triton accelerated kernels.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Signed-off-by: Daniel Korzekwa <dkorzekwa@nvidia.com>
2026-10-01 20:56:57 +02:00

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Announcements
#############
Release notes, technical updates, examples, and deployment stories from the Model Optimizer team.
.. raw:: html
<section class="announcement-section" aria-label="Announcement index">
<div class="announcement-toolbar">
<label class="announcement-search-label" for="announcement-search">Search announcements</label>
<input id="announcement-search" class="announcement-search" type="search" placeholder="Search announcements" autocomplete="off" />
<div class="announcement-tags" aria-label="Announcement tags">
<button class="announcement-tag is-active" type="button" data-tag="all" aria-pressed="true">All</button>
<button class="announcement-tag" type="button" data-tag="release" aria-pressed="false">Release</button>
<button class="announcement-tag" type="button" data-tag="autoquantize" aria-pressed="false">AutoQuantize</button>
<button class="announcement-tag" type="button" data-tag="quantization" aria-pressed="false">Quantization</button>
<button class="announcement-tag" type="button" data-tag="nvfp4" aria-pressed="false">NVFP4</button>
<button class="announcement-tag" type="button" data-tag="qad" aria-pressed="false">QAD</button>
<button class="announcement-tag" type="button" data-tag="local-hessian" aria-pressed="false">Local-Hessian</button>
<button class="announcement-tag" type="button" data-tag="speculative-decoding" aria-pressed="false">Speculative decoding</button>
<button class="announcement-tag" type="button" data-tag="dflash" aria-pressed="false">DFlash</button>
<button class="announcement-tag" type="button" data-tag="dspark" aria-pressed="false">DSpark</button>
<button class="announcement-tag" type="button" data-tag="domino" aria-pressed="false">Domino</button>
<button class="announcement-tag" type="button" data-tag="architecture" aria-pressed="false">Architecture</button>
<button class="announcement-tag" type="button" data-tag="docs" aria-pressed="false">Docs</button>
<button class="announcement-tag" type="button" data-tag="github-pages" aria-pressed="false">GitHub Pages</button>
</div>
</div>
<div class="announcement-grid" id="announcement-grid">
<article class="announcement-card" data-date="2026-09-16" data-title="Recovering W4A4 NVFP4 Accuracy with Quantization-Aware Distillation" data-summary="Weight-only NVFP4 is slower than BF16 on Blackwell; W4A4 unlocks the FP4 kernels, and QAD recovers the accuracy it costs." data-tags="quantization nvfp4 w4a4 qad distillation megatron-bridge">
<div class="announcement-card-meta">September 16, 2026 &middot; Model Optimizer Team</div>
<h2><a href="announcements/qwen36-w4a4-qad.html">Recovering W4A4 NVFP4 Accuracy with Quantization-Aware Distillation</a></h2>
<p>Weight-only NVFP4 is <em>slower</em> than BF16 on Blackwell. W4A4 beats it in 9 of 12 shapes, and QAD recovers the accuracy W4A4 costs on Qwen3.6-35B-A3B.</p>
<div class="announcement-card-tags"><span>quantization</span><span>nvfp4</span><span>w4a4</span><span>qad</span><span>distillation</span><span>megatron-bridge</span></div>
</article>
<article class="announcement-card" data-date="2026-09-09" data-title="Improving NVFP4 Accuracy with Local-Hessian Weight Scales" data-summary="How Local-Hessian selects NVFP4 block scales to minimize layer output error, and how it compares with max, MSE, Four-over-six, and GPTQ." data-tags="local-hessian quantization nvfp4 calibration modelopt">
<div class="announcement-card-meta">September 9, 2026 &middot; Model Optimizer Team</div>
<h2><a href="announcements/local-hessian.html">Improving NVFP4 Accuracy with Local-Hessian Weight Scales</a></h2>
<p>How Local-Hessian selects NVFP4 block scales to minimize layer output error, and how it compares with max, MSE, Four-over-six, and GPTQ.</p>
<div class="announcement-card-tags"><span>local-hessian</span><span>quantization</span><span>nvfp4</span><span>calibration</span><span>modelopt</span></div>
</article>
<article class="announcement-card" data-date="2026-08-24" data-title="AutoQuantize: A Fast Automatic Mixed-Precision Assignment" data-summary="AutoQuantize finds low-sensitivity mixed-precision assignments with gradient-based scoring under a modeled effective-bits budget." data-tags="autoquantize quantization mixed-precision modelopt">
<div class="announcement-card-meta">August 24, 2026 &middot; Model Optimizer Team</div>
<h2><a href="announcements/autoquantize.html">AutoQuantize: A Fast Automatic Mixed-Precision Assignment</a></h2>
<p>AutoQuantize finds low-sensitivity mixed-precision assignments with gradient-based scoring under a modeled effective-bits budget.</p>
<div class="announcement-card-tags"><span>autoquantize</span><span>quantization</span><span>mixed-precision</span><span>modelopt</span></div>
</article>
<article class="announcement-card" data-date="2026-08-13" data-title="Model Optimizer announcements are moving to GitHub Pages" data-summary="The public Model Optimizer site is gaining a PR-updated announcements landing page within the existing Sphinx documentation." data-tags="release docs github-pages">
<div class="announcement-card-meta">August 13, 2026 &middot; Model Optimizer Team</div>
<h2><a href="announcements/github-pages-announcements.html">Model Optimizer announcements are moving to GitHub Pages</a></h2>
<p>The GitHub Pages site now starts with announcements while the existing API documentation remains available in the docs navigation.</p>
<div class="announcement-card-tags"><span>release</span><span>docs</span><span>github-pages</span></div>
</article>
<article class="announcement-card" data-date="2026-07-13" data-title="DSpark vs Domino: Same DFlash Backbone, Different Correction Heads" data-summary="DSpark and Domino both build on block-parallel DFlash draft generation but diverge in their token-level correction heads." data-tags="speculative-decoding dflash dspark domino architecture">
<div class="announcement-card-meta">July 13, 2026 &middot; Model Optimizer Team</div>
<h2><a href="announcements/dspark-vs-domino.html">DSpark vs Domino: Same DFlash Backbone, Different Correction Heads</a></h2>
<p>DSpark and Domino share a DFlash backbone but make different correction-head tradeoffs: ModelOpt's <code>vanilla</code> Markov head versus a GRU.</p>
<div class="announcement-card-tags"><span>speculative-decoding</span><span>dflash</span><span>dspark</span><span>domino</span><span>architecture</span></div>
</article>
</div>
<p class="announcement-empty" id="announcement-empty" hidden>No announcements match this search.</p>
<nav class="announcement-pager" id="announcement-pager" aria-label="Announcement pages" hidden>
<button class="announcement-page-button" id="announcement-prev" type="button">Previous</button>
<span class="announcement-page-status" id="announcement-page-status"></span>
<button class="announcement-page-button" id="announcement-next" type="button">Next</button>
</nav>
</section>
.. toctree::
:hidden:
:maxdepth: 1
:caption: Announcements
self
.. toctree::
:hidden:
:glob:
:maxdepth: 1
:caption: Getting Started
getting_started/[0-9]*
Quick Start: PTQ - PyTorch <https://github.com/NVIDIA/Model-Optimizer/tree/main/examples/hf_ptq>
Quick Start: PTQ - ONNX <https://github.com/NVIDIA/Model-Optimizer/tree/main/examples/onnx_ptq>
Quick Start: PTQ - PyTorch to ONNX <https://github.com/NVIDIA/Model-Optimizer/tree/main/examples/torch_onnx>
Quick Start: PTQ - Windows <https://github.com/NVIDIA/Model-Optimizer/tree/main/examples/windows>
Quick Start: QAT and QAD <guides/quantization_aware_training_and_distillation>
Quick Start: Pruning <https://github.com/NVIDIA/Model-Optimizer/tree/main/examples/pruning>
Quick Start: Distillation <https://github.com/NVIDIA/Model-Optimizer/tree/main/examples/llm_distill>
Quick Start: Speculative Decoding <https://github.com/NVIDIA/Model-Optimizer/tree/main/examples/speculative_decoding>
Quick Start: Sparsity <https://github.com/NVIDIA/Model-Optimizer/tree/main/examples/llm_sparsity>
.. toctree::
:hidden:
:maxdepth: 1
:caption: Guides
guides/0_support_matrix
guides/1_quantization
guides/quantization_aware_training_and_distillation
guides/2_save_load
guides/3_pruning
guides/4_distillation
guides/5_speculative_decoding
guides/6_sparsity
guides/7_nas
guides/8_autocast
guides/9_autotune
guides/10_recipes
guides/11_config_system
.. toctree::
:hidden:
:glob:
:maxdepth: 1
:caption: Deployment
deployment/[0-9]*
.. toctree::
:hidden:
:glob:
:maxdepth: 1
:caption: Examples
examples/[0-9]*
.. toctree::
:hidden:
:glob:
:maxdepth: 1
:caption: Reference
reference/[0-9]*
.. toctree::
:hidden:
:glob:
:maxdepth: 1
:caption: Support
support/[0-9]*
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