Update README.md

README.md

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 A compact vision language model that you can pretrain and finetune on a single consumer GPU.
 
+## 🔍 Performance & Training Highlights
+
+- 📊 **VQAv2 Accuracy**:  
+  Achieves **56.91%** on VQAv2 dev/test — making MicroLLaVA one of the best-performing open-source language models with vision capabilities under **700M parameters**.
+
+- 🧠 **Parameter Budget**:
+  - 🗣️ Language Model: **MicroLLaMA (300M)**
+  - 👁️ Vision Encoder: **SigLIP2 (400M)**  
+  → **~700M total parameters**
+
+- 🏆 **Best in Class**:  
+  According to ChatGPT’s Deep Research Agent (Aug 2025):  
+  > *“No known open model below ~700M currently surpasses MicroLLaVA’s VQAv2 accuracy. Models that do perform better tend to have larger language components.”*
+
+- 🧪 **Ongoing Experiments**:
+  - 🔧 **Qwen3-0.6B + SigLIP2**  
+    → Training is **converging**, showing promising loss curves. (Qwen3-0.6B is significantly larger than MicroLLaMA.)
+  - ❌ **Gemma-3B-270M-IT + SigLIP2**  
+    → Training **did not converge**, likely due to instability, bugs, or poor alignment under current hyperparameters.
 
 ## 📰 News and Updates