# Running AV Reasoning Models Within Onboard Compute and Latency Limits

**URL:** <https://forums.developer.nvidia.com/t/running-av-reasoning-models-within-onboard-compute-and-latency-limits/388691>\
**Category:** Technical Blog\
**Created:** [November 10, 2026, 4:00pm UTC](https://forums.developer.nvidia.com/t/running-av-reasoning-models-within-onboard-compute-and-latency-limits/388691 "2026-11-10T16:00:21Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![jwitsoe](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/jwitsoe/32/16591_2.png) [@jwitsoe](https://forums.developer.nvidia.com/u/jwitsoe)\
**Post date:** [November 10, 2026, 4:00pm UTC](https://forums.developer.nvidia.com/t/running-av-reasoning-models-within-onboard-compute-and-latency-limits/388691/1 "2026-11-10T16:00:21Z")

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Originally published at: [Running AV Reasoning Models Within Onboard Compute and Latency Limits | NVIDIA Technical Blog](https://developer.nvidia.com/blog/running-av-reasoning-models-within-onboard-compute-and-latency-limits/)  
   
Autonomous vehicle (AV) developers need reasoning models that can operate within the compute and latency constraints of an onboard system. Larger models provide a foundation for developing these capabilities, but moving them into a vehicle requires additional work to reduce model size, preserve useful reasoning, and validate performance on the target hardware. NVIDIA Alpamayo 2…