Update README.md

README.md

@@ -500,6 +500,23 @@ This report summarizes the evaluation results of various emotion classification
 
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+## Model Variants
+
+BoltUIX offers a range of BERT-based models tailored to different performance and resource requirements. The `boltuix/bert-mobile` model is optimized for mobile and edge devices, offering strong performance with the ability to quantize to ~25 MB without significant loss. Below is a summary of available models:
+
+| Tier       | Model ID                | Size (MB) | Notes                                              |
+|------------|-------------------------|-----------|----------------------------------------------------|
+| Micro      | boltuix/bert-micro      | ~15 MB    | Smallest, blazing-fast, moderate accuracy          |
+| Mini       | boltuix/bert-mini       | ~17 MB    | Ultra-compact, fast, slightly better accuracy      |
+| Tinyplus   | boltuix/bert-tinyplus   | ~20 MB    | Slightly bigger, better capacity                  |
+| Small      | boltuix/bert-small      | ~45 MB    | Good compact/accuracy balance                     |
+| Mid        | boltuix/bert-mid        | ~50 MB    | Well-rounded mid-tier performance                 |
+| Medium     | boltuix/bert-medium     | ~160 MB   | Strong general-purpose model                      |
+| Large      | boltuix/bert-large      | ~365 MB   | Top performer below full-BERT                     |
+| Pro        | boltuix/bert-pro        | ~420 MB   | Use only if max accuracy is mandatory             |
+| Mobile     | boltuix/bert-mobile     | ~140 MB   | Mobile-optimized; quantize to ~25 MB with no major loss |
+
+For more details on each variant, visit the [BoltUIX Model Hub](https://huggingface.co/boltuix).
 
 
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