Add T2I 4-step model card overview

Summary: Add a concise Text2Image 4-step overview with links to the base model, PBR, Benchmarks, and Usage sections. Validation: git diff --check.

README.md

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 ## Description
 
+Cosmos3-Super-Text2Image-4Step is a 4-step distilled version of the base [Cosmos3-Super-Text2Image](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image) model. Given a text prompt, it generates a high-fidelity image.
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+- **What's different from the base model:** Distilled into a fixed 4-step sampling schedule without the need for classifier-free guidance. At the recommended 50-step + CFG setting for the Text2Image model, this replaces 50 × 2 = 100 model evaluations with 4, leading up to 25× fewer diffusion-model evaluations per image (see [PBR](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image-4Step#pbr-performance-benchmark-reporting) for latency estimates).
+- **Quality:** At just 4 steps, ranks #2 among open-source models on the Artificial Analysis Text-to-Image leaderboard, within one place of the full-step Cosmos3-Super-Text2Image (as of 2026/07/17; see [Benchmarks section](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image-4Step#benchmarks)).
+- **Input / Output:** Text prompt in → PNG image out. Supports various aspect ratios and resolutions.
+- **Example usage and output:** See [Usage](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image-4Step#usage-run-inference-with-vllm-omni) section.
+- **Hardware:** The 64B model needs a multi-GPU H100/H200 node (4–8 GPUs) or a single B200; it does not fit on a single smaller GPU. See [Usage](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image-4Step#usage-run-inference-with-vllm-omni). Full model details below.
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+Cosmos3-Super-Text2Image-4Step was developed by NVIDIA as a part of Cosmos3.
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 Cosmos3 is a collection of Omnimodal world models capable of generating dynamic, high-quality video, image, audio, and action commands from combinations of text, image, video, and action trajectory inputs. It serves as a foundational building block for a broad range of Physical AI applications and research spanning world understanding, world generation, simulation, and embodied policy learning.
 
 This model is ready for commercial and non-commercial use.