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+title: README
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-Moxin 7B: A Fully Open-Source 7B Language Model with Unprecedented Transparency
+Introducing Moxin 7B: The truly open, SOTA-performing LLM and VLM that's redefining transparency.
 
-We’re thrilled to unveil Moxin 7B, a new milestone in open large language model (LLM) development — designed to push the boundaries of performance and openness.
-
-In an era where many "open" LLMs lack true transparency (e.g., missing training code, data, or restrictive licenses), Moxin 7B sets a new gold standard by committing to full disclosure and reproducibility. 
-Developed under the Model Openness Framework (MOF), Moxin 7B achieves the top classification level of Open Science, thanks to:
-
-**What we’ve open-sourced**:
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-- Pre-training code, data, and Moxin Base model.
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-+ Post-training code, data, and Moxin Instruct model.
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-+ RL code with GRPO, data and Moxin Reasoning model.
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-**Performance Highlights**:
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-+ Zero-shot / Few-shot: Outperforms Mistral, Qwen, and LLaMA on tasks like HellaSwag, ARC, MMLU, and PIQA
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-+ Reasoning: Moxin-Reasoning-7B achieves superior performance on MATH-500, AMC, and OlympiadBench — proving reinforcement learning can work for small 7B models
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-+ Training cost: ~$160K for full pretraining — efficient and reproducible at scale
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-**Post-training Frameworks**:
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-+ SFT and DPO with Tülu 3
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-+ CoT-enhanced reasoning with GRPO via DeepScaleR
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-**Get the models and code**:
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-+ Base model: Moxin-LLM-7B
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-+ Instruction model: Moxin-Instruct-7B
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-+ Reasoning model: Moxin-Reasoning-7B
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-+ Code & docs: github.com/moxin-org/Moxin-LLM
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-+ Arxiv paper: https://arxiv.org/abs/2412.06845
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-We believe this is a step toward a more transparent, reproducible, and innovation-friendly AI ecosystem — especially for researchers, developers, and startups looking to build upon a robust, open foundation.
-Let’s build open AI the right way.
+We've open-sourced everything—pre-training code, data, and models, including our GRPO-enhanced Reasoning model. It outperforms Mistral, Qwen, and LLaMA in zero-shot/few-shot tasks and delivers superior reasoning on complex math benchmarks, all with an efficient training cost of ~$160K for full pretraining.
 
+We unleash the power of reproducible AI 🚀. Interested? Explore the models and code on our [GitHub](https://github.com/moxin-org/Moxin-LLM) and read the full paper on [arXiv](https://arxiv.org/abs/2412.06845).