Update performance numbers to the 100-clip benchmark
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README.md
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[](https://z-lab.ai/projects/flashdrive/)
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[](https://huggingface.co/collections/z-lab/flashdrive)
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[FlashDrive](https://github.com/z-lab/flashdrive) accelerates [Alpamayo 1 (R1)](https://huggingface.co/nvidia/Alpamayo-R1-10B) — one of NVIDIA's 10B-parameter vision-language-action models for autonomous driving — by **
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This repository mirrors the weights of [nvidia/Alpamayo-R1-10B](https://huggingface.co/nvidia/Alpamayo-R1-10B) and is the **base checkpoint** of the FlashDrive stack. Loading it pulls the derived companions automatically:
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## Performance
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On a single RTX PRO 6000, FlashDrive runs Alpamayo 1 (R1) at **
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## License
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[](https://z-lab.ai/projects/flashdrive/)
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[](https://huggingface.co/collections/z-lab/flashdrive)
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[FlashDrive](https://github.com/z-lab/flashdrive) accelerates [Alpamayo 1 (R1)](https://huggingface.co/nvidia/Alpamayo-R1-10B) — one of NVIDIA's 10B-parameter vision-language-action models for autonomous driving — by **4.3× with no loss in accuracy**, through streaming inference, [DFlash](https://github.com/z-lab/dflash) speculative reasoning, [ParoQuant](https://github.com/z-lab/paroquant) W4A8 quantization, adaptive action caching, and `torch.compile`.
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This repository mirrors the weights of [nvidia/Alpamayo-R1-10B](https://huggingface.co/nvidia/Alpamayo-R1-10B) and is the **base checkpoint** of the FlashDrive stack. Loading it pulls the derived companions automatically:
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## Performance
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On a single RTX PRO 6000, averaged over 100 PhysicalAI-AV clips, FlashDrive runs Alpamayo 1 (R1) at **4.3× lower latency** (826 → 194 ms per window) while minADE improves from 1.838 to 1.662. See the [repository](https://github.com/z-lab/flashdrive#performance) for the full benchmark.
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## License
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