Flash Vision-Language-Action Inference for Autonomous Driving FlashDrive accelerates Alpamayo 1.5 — one of NVIDIA's 10B-parameter vision-language-action models for autonomous driving — by 4.7× with no loss in accuracy, through streaming inference, DFlash speculative reasoning, ParoQuant W4A8 quantization, adaptive action caching, and torch.compile. This repository mirrors the weights of nvidia/Alpamayo-1.5-10B and is the base checkpoint of the FlashDrive stack. Loading it pulls the derived companions automatically: Install FlashDrive, then load this base checkpoint — the -PARO and -DFlash companions are fetched automatically: The first call per stream only prefills the KV cache and returns…
Open weights
other
11.1B parameters
Flash Vision-Language-Action Inference for Autonomous Driving DFlash draft model for z-lab/Alpamayo-1.5-10B, used by FlashDrive to accelerate the chain-of-causation reasoning of Alpamayo 1.5. DFlash (ICML 2026) uses a lightweight block-diffusion draft to propose several tokens in parallel; the target verifies each block in a single forward, preserving its output distribution. This draft is a 2-layer Qwen3-style network (block size 8) conditioned on target hidden states from layers 24/30/31/32/34. The repository also ships maskembedding.pt, the trained mask-token embedding FlashDrive appends to the target's embedding table. See the base model card and the FlashDrive repository for the full…
Open weights
other
470M parameters
40,960 tokens
