TurboVLA: Real-Time Vision-Language-Action Model at 32 Hz on an RTX 4090 with <1 GB VRAM
Vision-language-action (VLA) models commonly adopt an LLM-centric $V \to L \to A$ pathway, processing visual observations and language instructions through a large language model before predicting robot actions. Although effective, this design incurs substantial computation and memory overhead. In this work, we introduce TurboVLA, a compact VLA architecture built on a direct $V + L \to A$ mapping. Instead of using a large language model as the central interface between perception and action, TurboVLA independently encodes visual observations and language instructions, directly exchanges information between them through lightweight bidirectional vision-language interaction, and predicts co...
| Authors | Hengyi Xie, Chenfei Yao, Xianjin Wu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 29 July 2026 |
| Last updated at source | 27 September 2026 |
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- H-EmbodVis/TurboVLAModel · cited by
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