[14/x] docs update: improve workflows page#3790
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/3790
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Jan 30, 2026
| | A100 | int4 | bfloat16 | ⚪ | 🟢 [(link)](qat.md) | 🟡: [HQQ](https://github.com/pytorch/ao/tree/main/torchao/prototype/hqq/README.md), [AWQ](https://github.com/pytorch/ao/tree/main/torchao/prototype/awq) | 🟢 [(link)](https://github.com/pytorch/ao/tree/main/torchao/quantization#a16w4-weightonly-quantization) | | ||
| | A100 | int8 | bfloat16 | ⚪ | 🟢 [(link)](qat.md) | ⚪ | 🟢 [(link)](https://github.com/pytorch/ao/tree/main/torchao/quantization#a16w8-int8-weightonly-quantization) | | ||
| | A100 | int8 | int8 | 🟡 [(link)](https://github.com/pytorch/ao/tree/main/torchao/prototype/quantized_training) | 🟢 [(link)](qat.md) | ⚪ | 🟢 [(link)](https://github.com/pytorch/ao/tree/main/torchao/quantization#a8w8-int8-dynamic-quantization) | | ||
| | B200 | nvfp4 | nvfp4 | 🟠 | 🟡 [(link)](https://github.com/pytorch/ao/blob/main/torchao/prototype/qat/nvfp4.py) | ⚪ | 🟡 [(link)](https://github.com/pytorch/ao/tree/main/torchao/prototype/mx_formats#mx-inference) | |
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maybe:
first group by hardware (B200, H100, A100), then by stable -> prototype -> planned?
seems closer to how user will use it
This was referenced Jan 30, 2026
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Summary:
future PRs will move training and inference README files to the docs
Test Plan: