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README.md

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+---
+pipeline_tag: robotics
+library_name: transformers
+license: other
+language:
+- en
+base_model:
+- nvidia/Alpamayo-R1-10B
+tags:
+- flashdrive
+- autonomous-driving
+- vision-language-action
+- alpamayo
+new_version: z-lab/Alpamayo-1.5-10B
+---
+
+# Alpamayo-R1-10B (FlashDrive)
+
+[Blog](https://z-lab.ai/projects/flashdrive/) | [GitHub](https://github.com/z-lab/flashdrive)
+
+**FlashDrive** is an algorithm-system co-design inference framework for
+[Alpamayo](https://huggingface.co/nvidia/Alpamayo-1.5-10B), NVIDIA's 10B-parameter
+vision-language-action (VLA) models for autonomous driving. It combines streaming VLM
+inference, [DFlash](https://github.com/z-lab/dflash) speculative reasoning, adaptive action
+caching, [ParoQuant](https://github.com/z-lab/paroquant) W4A8 quantization, and system
+optimizations to accelerate inference while preserving accuracy.
+
+This repository mirrors the weights of
+[nvidia/Alpamayo-R1-10B](https://huggingface.co/nvidia/Alpamayo-R1-10B) and serves as the
+**base checkpoint** of the FlashDrive stack. FlashDrive derives the companion checkpoints
+from this repo id by suffix:
+
+| Repository | Contents |
+|---|---|
+| [z-lab/Alpamayo-R1-10B-PARO](https://huggingface.co/z-lab/Alpamayo-R1-10B-PARO) | W4A8 (ParoQuant) language-model weights |
+| [z-lab/Alpamayo-R1-10B-DFlash](https://huggingface.co/z-lab/Alpamayo-R1-10B-DFlash) | DFlash block-diffusion draft model |
+
+## Quick Start
+
+Install [FlashDrive](https://github.com/z-lab/flashdrive), then load the base checkpoint —
+the `-PARO` and `-DFlash` companions are derived from it by suffix and fetched automatically:
+
+```python
+from flashdrive import load_flashdrive_model
+
+model = load_flashdrive_model("z-lab/Alpamayo-R1-10B")
+
+pred_xyz, pred_rot = model.sample_trajectories_streaming(data)
+```
+
+The first call per stream only prefills the KV cache and returns `(None, None)`.
+For an end-to-end benchmark on a PhysicalAI-AV clip:
+
+```bash
+python scripts/infer.py --model_path z-lab/Alpamayo-R1-10B
+```
+
+## Performance
+
+FlashDrive delivers a comparable speedup on Alpamayo 1 (R1); see the [FlashDrive repository](https://github.com/z-lab/flashdrive) for benchmarks.
+
+## License
+
+These weights are derived from NVIDIA's Alpamayo release and remain governed by its
+[non-commercial license](https://huggingface.co/nvidia/Alpamayo-R1-10B/blob/main/LICENSE).
+The [FlashDrive](https://github.com/z-lab/flashdrive) inference code is MIT.
+
+## Citation
+
+```bibtex
+@article{li2026flashdrive,
+      title={FlashDrive: Flash Vision-Language-Action Inference For Autonomous Driving},
+      author={Zekai Li, Yihao Liang, Hongfei Zhang, Jian Chen, Yesheng Liang, Zhijian Liu},
+      year={2026}
+}
+```