Compare image models for scientific figures
Compare three model strengths for three different scientific figure jobs, then choose the best fit before you start generating.
Available Models
Three model paths inside SciFig
Each model is useful, but not in the same way. Default to GPT Image 2 for journal submission; switch to Nano Banana Pro for slides and posters; pick Nano Banana 2 for routine work.
GPT Image 2
The recommended default — strongest on chemistry notation, abstract math, long-prompt label fidelity, and journal-grade scientific figures.
Nano Banana Pro
The editorial-style specialist — strongest on readability and aesthetic polish, ideal when BioRender-style simplification beats notation rigor.
Nano Banana 2
The balanced daily-driver for routine figure work — internal drafts, repeated redraws, lab-meeting visuals, and recurring pathway figures.
How to Choose
What each model is best at
Choose the model that fits your figure task — journal submission, editorial polish, or balanced everyday speed.
GPT Image 2 — Recommended Default
- Best for chemistry rigor — renders standard chemistry conventions (transition states, stereochemistry, reaction mechanisms) reliably.
- Best for abstract math and topology — handles Möbius surfaces, parametric equations, and 3D geometry where conceptual accuracy matters.
- Best for long, dense prompts — every requested label, formula, and scale bar must land in the figure.
Nano Banana Pro — Editorial-Style Specialist
- Best for slide decks and conference posters where readability beats annotation density.
- Best for BioRender-style simplified mechanism figures (clean step-by-step diagrams).
- Best for ML/CS architecture diagrams where layer-stacking visual feel matters more than text fidelity.
Nano Banana 2 — Balanced Everyday
- Best as a balanced all-around model for routine figure work.
- Best for repeatable day-to-day use across multiple modes.
- Best when you want practical speed-quality balance instead of a specialized edge.