# smolvla

Published articles for smolvla.

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## Bringing Robotics AI to Embedded Platforms: Dataset Recording, VLA Fine-Tuning, and On-Device Optimizations

DevFeed: [Bringing Robotics AI to Embedded Platforms: Dataset Recording, VLA Fine-Tuning, and On-Device Optimizations](<https://devfeed.tech/articles/bringing-robotics-ai-to-embedded-platforms-dataset-recording-vla-fine-tuning-and-on-device-optimizations-7404.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/nxp/bringing-robotics-ai-to-embedded-platforms>)

Author: Gaetan Bahl; Enzo Ruedas; Tess Boivin

Published: 2026-03-05T14:16:49Z

Content type: tutorial

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [Robotics](<https://devfeed.tech/topics/robotics.md>), [Fine-tuning](<https://devfeed.tech/topics/fine-tuning.md>), [multimodal](<https://devfeed.tech/topics/multimodal.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [systems](<https://devfeed.tech/topics/systems.md>), [AI Inference](<https://devfeed.tech/topics/ai-inference.md>), [SOC](<https://devfeed.tech/topics/soc.md>), [data](<https://devfeed.tech/topics/data.md>), [Hardware](<https://devfeed.tech/topics/hardware.md>), [smolvla](<https://devfeed.tech/topics/smolvla.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [best-practices](<https://devfeed.tech/tags/best-practices.md>), [compression](<https://devfeed.tech/tags/compression.md>), [compute](<https://devfeed.tech/tags/compute.md>), [data](<https://devfeed.tech/tags/data.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [embedded](<https://devfeed.tech/tags/embedded.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [fine-tuning](<https://devfeed.tech/tags/fine-tuning.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [inference](<https://devfeed.tech/tags/inference.md>), [latency](<https://devfeed.tech/tags/latency.md>), [models](<https://devfeed.tech/tags/models.md>), [on-device](<https://devfeed.tech/tags/on-device.md>), [performance](<https://devfeed.tech/tags/performance.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [robotics](<https://devfeed.tech/tags/robotics.md>), [smolvla](<https://devfeed.tech/tags/smolvla.md>), [soc](<https://devfeed.tech/tags/soc.md>), [systems-engineering](<https://devfeed.tech/tags/systems-engineering.md>)

### AI overview

A practical guide to deploying Vision-Language-Action models on embedded robotic platforms. It covers reliable dataset recording, fine-tuning ACT and SmolVLA policies, asynchronous inference, latency-aware scheduling, and real-time optimization on the NXP i.MX 95 SoC.

### Source excerpt

Bringing Robotics AI to Embedded Platforms: Dataset Recording, VLA Fine-Tuning, and On-Device Optimizations Authors: Enzo Ruedas, Tess Boivin Recent advances in Large Language Models have enabled the transition from text-only reasoning to multimodal systems. First, with the integration of visual perception in Vision-Language Models (VLMs), and more recently with the generation of robot actions in Vision-Language-Action (VLA) models.

## Asynchronous Robot Inference: Decoupling Action Prediction and Execution

DevFeed: [Asynchronous Robot Inference: Decoupling Action Prediction and Execution](<https://devfeed.tech/articles/asynchronous-robot-inference-decoupling-action-prediction-and-execution-7111.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/async-robot-inference>)

Author: Francesco Capuano; Steven Palma; Michel Aractingi; Mustafa Shukor; Dana Aubakirova; Adil Zouitine; Simon Alibert; Remi Cadene

Published: 2025-07-10T00:00:00Z

Content type: tutorial

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [Processes](<https://devfeed.tech/topics/processes.md>)

Tags: [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [communication](<https://devfeed.tech/tags/communication.md>), [inference](<https://devfeed.tech/tags/inference.md>), [latency](<https://devfeed.tech/tags/latency.md>), [lerobot](<https://devfeed.tech/tags/lerobot.md>), [model](<https://devfeed.tech/tags/model.md>), [models](<https://devfeed.tech/tags/models.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [performance](<https://devfeed.tech/tags/performance.md>), [policy](<https://devfeed.tech/tags/policy.md>), [processes](<https://devfeed.tech/tags/processes.md>), [rest-api](<https://devfeed.tech/tags/rest-api.md>), [robotics](<https://devfeed.tech/tags/robotics.md>), [smolvla](<https://devfeed.tech/tags/smolvla.md>), [speed](<https://devfeed.tech/tags/speed.md>), [tutorial](<https://devfeed.tech/tags/tutorial.md>)

### AI overview

The article explains asynchronous robot inference, which separates action prediction from execution so robots can replan while continuing to act. It describes a two-process architecture and reports faster task completion with comparable success rates for SmolVLA.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## SmolVLA: Efficient Vision-Language-Action Model trained on Lerobot Community Data

DevFeed: [SmolVLA: Efficient Vision-Language-Action Model trained on Lerobot Community Data](<https://devfeed.tech/articles/smolvla-efficient-vision-language-action-model-trained-on-lerobot-community-data-7483.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/smolvla>)

Author: Dana Aubakirova; Andres Marafioti; merve; Aritra Roy Gosthipaty; Francesco Capuano; Loubna Ben Allal; Pedro Cuenca; Mustafa Shukor; Remi Cadene

Published: 2025-06-03T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [AI, ML & Data Engineering](<https://devfeed.tech/topics/ai-ml-data-engineering.md>)

Tags: [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [community](<https://devfeed.tech/tags/community.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [inference](<https://devfeed.tech/tags/inference.md>), [lerobot](<https://devfeed.tech/tags/lerobot.md>), [model](<https://devfeed.tech/tags/model.md>), [models](<https://devfeed.tech/tags/models.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [robotics](<https://devfeed.tech/tags/robotics.md>), [smolvla](<https://devfeed.tech/tags/smolvla.md>), [vision](<https://devfeed.tech/tags/vision.md>)

### AI overview

SmolVLA is a 450M open-source vision-language-action model for robotics trained on community-shared LeRobot data. The article presents its simulation and real-world results, consumer-hardware focus, and asynchronous inference support.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.