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update mapping table and what's new for v3.6 (#2308)
Signed-off-by: Huang, Tai <tai.huang@intel.com>
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README.md

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* Collaborate with cloud marketplaces such as [Google Cloud Platform](https://console.cloud.google.com/marketplace/product/bitnami-launchpad/inc-tensorflow-intel?project=verdant-sensor-286207), [Amazon Web Services](https://aws.amazon.com/marketplace/pp/prodview-yjyh2xmggbmga#pdp-support), and [Azure](https://azuremarketplace.microsoft.com/en-us/marketplace/apps/bitnami.inc-tensorflow-intel), software platforms such as [Alibaba Cloud](https://www.intel.com/content/www/us/en/developer/articles/technical/quantize-ai-by-oneapi-analytics-on-alibaba-cloud.html), [Tencent TACO](https://new.qq.com/rain/a/20221202A00B9S00) and [Microsoft Olive](https://github.com/microsoft/Olive), and open AI ecosystem such as [Hugging Face](https://huggingface.co/blog/intel), [PyTorch](https://pytorch.org/tutorials/recipes/intel_neural_compressor_for_pytorch.html), [ONNX](https://github.com/onnx/models#models), [ONNX Runtime](https://github.com/microsoft/onnxruntime), and [Lightning AI](https://github.com/Lightning-AI/lightning/blob/master/docs/source-pytorch/advanced/post_training_quantization.rst)
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## What's New
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* [2025/10] [MXFP8 / MXFP4 quantization](./docs/source/3x/PT_MXQuant.md) experimental support
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* [2025/09] FP8 dynamic quantization, including Linear, FusedMoE on Intel Gaudi AI Accelerators
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* [2025/05] FP8 static quantization of DeepSeek V3/R1 model on Intel Gaudi AI Accelerators
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* [2025/03] VLM quantization in transformers-like API on Intel CPU/GPU
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* [2024/10] [Transformers-like API](./docs/source/3x/transformers_like_api.md) for INT4 inference on Intel CPU and GPU.
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* [2024/07] From 3.0 release, framework extension API is recommended to be used for quantization.
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* [2024/07] Performance optimizations and usability improvements on [client-side](./docs/source/3x/client_quant.md).
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## Installation
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Choose the necessary framework dependencies to install based on your deploy environment.

docs/source/3x/gaudi_version_map.md

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</tbody>
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<tr>
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<td>v3.5</td>
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<td>v3.5, v3.6</td>
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<td>v1.22</td>
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</tr>
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</tbody>

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