A lite image model trades resolution and fine detail for cost and speed: Nano Banana 2 Lite outputs at 1K resolution but costs 3 cents per image and generates 2.5x faster than Nano Banana 2 — half its price, and a quarter of Nano Banana Pro's. Use lite for high-volume exploration, then escalate only selected assets to the full model.
Treat the trade-off as a workflow split, not a quality verdict: the lite tier is built for volume, the full tier for finals.
What you gain with lite: cost and speed. Nano Banana 2 Lite runs at 3 cents per image — 1,000 images for $30 — at half the cost of Nano Banana 2 and four times cheaper than Nano Banana Pro at 1,000-image volume, with 4-second generations that are 2.5x faster than the standard model. At that price point you stop budgeting individual generations: producing 10 options instead of one becomes the rational default, and a D2C team can test 50 ad concept variants instead of 5 to find the winning creative and cut acquisition cost.
What you give up: resolution and headroom for demanding shots. Lite caps output at 1K resolution — a deliberate design trade-off, not a quality failure — which rules it out for print-scale delivery, hero assets, and technically demanding frames. That's why lite models belong at the pre-production stage rather than as final-output models: mood boards, pre-visualization frames, product mockups, and draft rounds. For a filmmaker, iterating on 20 mood boards used to be a budget conversation; on lite pricing it's effectively free, and internal agency draft-review costs largely disappear.
What you don't give up as much as you'd expect: per-image quality. The old assumption that cheap means worse no longer holds — on Google's own benchmarks, Nano Banana Lite outperforms Nano Banana Pro on text-to-image quality. The full model's advantage is concentrated in resolution, fine detail, and hard shots, not in everyday prompt fidelity.
How to run both: a two-tier escalation workflow. Do all exploration, concept testing, and drafts on the lite model, then re-render only the chosen frames on Nano Banana Pro for final production quality — "only the ones that are chosen get escalated." The practical bottleneck at lite-model volume isn't generation speed but losing track of creative direction across dozens of outputs; inside invideo, the invideo agent holds your character sheets and brand context in persistent memory and routes each generation to the right tier — Lite for volume, Pro for finals — so you brief once instead of re-briefing every batch. Since every roster image model (Nano Banana tiers, Recraft, GPT-Image-2) runs on the same platform, the escalation step is a routing decision, not a tool switch.
Watch some of these to see what works for you:
It's not a better image. It's a thousand fast and cheap attempts to find the right idea, which, if your job is output, is the game changer
— invideo's creative team