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README.md

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-# Welcome to SiMa.ai on Hugging Face
 
-SiMa.ai is the **Physical AI** company. We provide the industry’s most power-efficient platform for deploying high-performance AI at the edge. 
+# SiMa.ai | Scaling Physical AI at the Edge
 
-This organization hosts **compiled and optimized model weights** specifically tailored for the SiMa.ai **Modalix™ MLSoC**.
+SiMa.ai provides a purpose-built platform for deploying high-performance AI models for vision, audio, and generative applications at the edge with industry-leading power efficiency.
 
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-
-## Our Model Library
-
-Our models are optimized using the SiMa.ai **LLiMa** framework to ensure maximum throughput with minimal power consumption.
-
-### Generative AI (LLMs)
-We provide edge-optimized versions of leading architectures:
-* **Llama 3.2 / 3.1** (3B, 8B)
-* **Qwen3 / Qwen2.5**
-* **Phi-3.5-mini**
-* **Mistral-7B-v0.3**
-* **Gemma3**
-
-### Vision-Language Models (VLMs)
-Enable real-time visual reasoning and "Physical AI" capabilities:
-* **Gemma 3** (4B)
-* **Qwen3-VL / Qwen2.5-VL** (3B,4B,7B,8B)
-* **LFM2-VL** (450M, 1.6B, 3B)
+Download our pre-optimized, ready-to-deploy models for the **Modalix™ MLSoC** below.
 
-### Speech Processing (ASR/TTS)
-* **Whisper:** Optimized for real-time, low-latency transcription on edge hardware.
-
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-
-## Technical Note: `a16w4`
-Most models in this repo use **a16w4** quantization (16-bit Activations, 4-bit Weights). This configuration is specifically tuned to leverage the proprietary hardware accelerators within the SiMa.ai MLSoC, providing the best "Performance per Watt" in the industry.
-
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+* **Vision-Language (VLMs):** Gemma 3, Qwen2.5-VL, Qwen3-VL, and LFM2-VL.
+* **Generative AI (LLMs):** Llama 3.2/3.1, Phi-3.5-mini, and Mistral-7B, Qwen2.5/3, Gemma
+* **Audio & Speech:** Whisper
 
-## Getting Started
-1. **Explore:** Browse our [Models tab](https://huggingface.co/simaai/models) to find the architecture you need.
-2. **Compile & Deploy:** Use our [LLiMa Framework](https://docs.sima.ai/pages/genai/main.html) to integrate these weights into your edge application.
-3. **Hardware:** Learn more about the [Modalix™ MLSoC](https://sima.ai/mlsoc-family/).
+### Deployment & Tools
+* Models are optimized using **LLiMa** (Automated Code Generation) for **sub-10W inference**.
+* Deployment supports **a16w4** and **Hybrid a16w8/4** quantization to maximize Performance-per-Watt.
+* Join our [Developer Portal](https://developer.sima.ai/) or visit our [GitHub](https://github.com/SiMa-ai/) for documentation and SDK access.
 
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-[Website](https://sima.ai) | [GitHub](https://github.com/SiMa-ai/) | [Contact Support](https://sima.ai/contact-us/)
+[Website](https://sima.ai) | [Contact Support](https://sima.ai/contact-us/)