Update README.md

README.md

@@ -13,6 +13,22 @@ library_name: torchao
 pipeline_tag: text-to-3d
 ---
 
+## 🚀 First INT4 Quantized Cube3D — Run on Half the VRAM
+
+![](https://img.shields.io/badge/VRAM_-14.3_GB_(44%25↓)-brightgreen)
+![](https://img.shields.io/badge/Loading-88%25_faster-blue)
+![](https://img.shields.io/badge/Latency-same-green)
+
+Presenting the **first INT4 quantized version** of [Cube3D v0.5](https://huggingface.co/Roblox/cube3d-v0.5), a text-to-3D mesh generative model. Quantized via **RTN W4A16** (group_size=128) using [torchao](https://github.com/pytorch/ao), it cuts peak VRAM from **25.4 GB → 14.3 GB (44%↓)** while maintaining the same inference speed and comparable shape fidelity — enabling 3D shape generation on much smaller, more accessible GPUs.
+
+| | BF16 + Engine | BF16 + EngineFast | **INT4 + EngineFast** |
+|---|:-:|:-:|:-:|
+| ⏱️ Latency | 90.9 s | 15.0 s | **14.2 s** |
+| 🎮 Peak VRAM | 21.7 GB | 25.4 GB | **14.3 GB (44%↓)** ✨ |
+| 📦 Setup time | 19.4 s | 206.9 s | **25.1 s (88%↓)** |
+
+> 💡 The 44% VRAM reduction means this model now fits on a single 16 GB GPU (e.g. NVIDIA L4, A10 etc.), bringing high-quality text-to-3D generation to individual researchers and end-user hardware.
+
 # Cube3D v0.5 — RTN W4A16 INT4 (torchao)
 
 Post-training quantized version of [Roblox/cube3d-v0.5](https://huggingface.co/Roblox/cube3d-v0.5), a text-to-3D mesh generative model.  
@@ -31,15 +47,7 @@ The BF16 GPT weights (`shape_gpt.safetensors`) are **not** included here — the
 
 ## Benchmark (NVIDIA A100-SXM4-40GB, 15-categories)
 
-| Config | Mean latency | Peak VRAM | Setup time |
-|--------|-------------|-----------|------------|
-| BF16 + Engine (baseline) | 90.9 s | 21.7 GB | 19.4 s |
-| BF16 + EngineFast | 15.0 s | 25.4 GB | 206.9 s |
-| **INT4 + EngineFast** | **14.2 s (84%↓)** | **14.3 GB (44%↓)** | **25.1 s (88%↓)** |
-
-INT4 EngineFast vs BF16 Engine: **84% faster inference**, **44% less peak VRAM**, **88% faster loading**.
-
-## Shape quality (Chamfer Distance, 15 categories, 170 prompts)
+### Shape Quality (Chamfer Distance, 15 categories, 170 prompts):
 
 Median CD: 67.9 × 10⁻³