SmolVLM Grows Smaller – Introducing the 256M & 500M Models!

SmolVLM - small yet mighty Vision Language Model

SmolLM - blazingly fast and remarkably powerful

Investing in Performance: Fine-tune small models with LLM insights - a CFM case study

When Faster VLA Deployment Changes Closed-Loop Behavior: Task Success-Latency Analysis of SmolVLA Across PyTorch and ONNX Variants

arXiv:2609.14146v1 Announce Type: cross Abstract: Vision-language-action (VLA) deployment can reduce inference latency while changing closed-loop task behavior. We evaluate HuggingFaceVLA/smolvla_lib...

Finer is Better (with the Right Scaling)

arXiv:2605. 08565v2 Announce Type: replace Abstract: Microscaling is a critical technique for preserving the quality of Large Language Models (LLMs) quantized to ultra-low precision formats.

Accelerate your models with 🤗 Optimum Intel and OpenVINO