Open VLM Leaderboard

What is Open VLM Leaderboard?

Open VLM Leaderboard is your go-to hub for comparing the performance of Vision-Language Models (VLMs) across diverse benchmarks and datasets. Think of it as a dynamic scoreboard that helps researchers, developers, and AI enthusiasts track which models excel at tasks like image captioning, visual question answering, or cross-modal retrieval. Whether you're fine-tuning your own VLM or just curious about the state of the art, this tool makes it easy to explore evaluation results from VLMEvalKit in one centralized, interactive space.

Key Features

• Smart filtering – Narrow results by dataset, task type, or model architecture to find exactly what you need
• Interactive visualizations – Dive into side-by-side comparisons with intuitive charts that update in real time
• Real-time updates – Stay ahead with automatic syncs whenever new evaluation data gets added to VLMEvalKit
• Model deep-dive profiles – Click any model to see detailed metrics, training specifics, and citation links
• Customizable rankings – Prioritize performance scores, efficiency metrics, or fairness benchmarks based on your priorities
• Cross-framework compatibility – Compare models built with different frameworks (PyTorch, TensorFlow, etc.) on equal footing
• Community-driven insights – See which models are trending through user-upvoted highlights and discussion threads
• Benchmark explainers – New to a dataset? Hover over icons to get plain-language summaries of what each benchmark tests

How to use Open VLM Leaderboard?

1. Access the platform – Open your browser and navigate to the Open VLM Leaderboard interface
2. Apply filters – Use the sidebar to select specific tasks (e.g., "image-text retrieval") or datasets (e.g., "COCO")
3. Explore visualizations – Toggle between bar charts, radar plots, or scatter graphs to spot patterns
4. Compare models – Check boxes next to models to highlight their performance differences
5. Drill down – Click individual entries to view technical specs, training details, and paper links
6. Track updates – Enable notifications to get alerts when new models or benchmarks appear
7. Share findings – Generate shareable links with pre-set filters for collaboration or presentations
8. Contribute data – Submit your own evaluation results via the VLMEvalKit integration (if authorized)

Frequently Asked Questions

Why does the leaderboard show different rankings for the same model across datasets?
That's the whole point! Models often specialize - for example, one might crush medical imaging tasks but struggle with everyday objects. The leaderboard helps you spot these nuances.

How often does the leaderboard refresh with new models?
It pulls data directly from VLMEvalKit, so updates happen automatically whenever researchers submit new evaluations. You'll never see stale info!

Can I customize which metrics get prioritized in rankings?
Absolutely! Want to focus on energy efficiency instead of raw accuracy? Just adjust the metric weights in your profile settings.

Where does the evaluation data actually come from?
All data flows from VLMEvalKit, an open-source framework that standardizes how VLMs get tested. This ensures apples-to-apples comparisons across the board.

Is there a way to compare multiple models at once visually?
You bet! Use the "Compare" feature to generate side-by-side radar charts that highlight strengths and weaknesses across 8+ metrics simultaneously.

What if I don't understand a technical term used in a model's profile?
Hover over any term with a dotted underline (like "zero-shot accuracy") to get a quick pop-up explanation written for non-experts.

Can I export visualization charts for my research paper?
Yes! Every chart has a "Download as SVG" button, and you can tweak color schemes to match your publication's style guide.

How does the leaderboard handle models with incomplete benchmark data?
It's smart about gaps - missing metrics get grayed-out placeholders, and you can sort results by "completeness score" to find the most thoroughly tested models.