UVLM v4.0.0 — Gemma 4, the Transformers 5 Migration, and Why This One Is a Major Version
Highlights New model family: Gemma 4 (Google [...]
UVLM v3.2.0 — InternVL3.5 Joins the Registry, With Zero Notebook Changes
UVLM v3.2.0 adds InternVL3.5 (1B–38B, six checkpoints): 21 open VLM checkpoints across 4 families, one Python interface. The new family appeared in the notebooks without a single notebook edit — plus per-model output files for cleaner benchmarking.
UVLM v3.1.0 — Qwen3-VL Joins the Registry, With Family-Based Model Selection
UVLM v3.1.0 adds a third model family, Qwen3-VL (2B–32B Instruct), bringing the registry to 15 checkpoints. The notebooks gain a two-level family/model selector, the loader picks BF16 automatically on capable GPUs, and the smallest new model runs in about 2 GB of VRAM. Same three-block workflow, same prompts, one more family to compare.
SAGAI v2.0 — A Unified Multi-Model Notebook for Streetscape Analysis
SAGAI v2.0 consolidates the full streetscape analysis pipeline into a single Google Colab notebook and replaces the inline LLaVA-only inference code with the UVLM package, enabling multi-model benchmarking across 11 VLM checkpoints. New features include a multi-task prompt builder, consensus validation with majority voting, chain-of-thought reasoning, truncation detection, interactive Folium maps, view-direction filtering, and support for loading existing polygons as study area boundaries.
UVLM v3.0.0: From Colab Notebook to Python Package — Run Vision-Language Models Anywhere
UVLM v3.0.0 turns a Colab notebook into a full Python package. Run vision-language models locally, in notebooks, or scripts with a simple API and no setup complexity.
Introducing UVLM: A Free Tool to Compare AI Models That Understand Images
UVLM is a free, open-source tool for loading, testing, and comparing Vision-Language Models on custom image analysis tasks. Running entirely in Google Colab, it lets researchers and practitioners benchmark multiple AI models using the same prompts and images — no coding, no GPU ownership, no model-specific pipelines. This post explains what VLMs are, why comparing them matters, and how to get started in five minutes.