Can AI automatically select the best model for each scene in a video project?

Yes. The invideo agent routes each scene to the best-fit model automatically — picking from Veo, Kling, Seedance 2.0, Recraft, Nano Banana, and GPT-Image-2 based on what the shot actually needs (lighting realism, text rendering, motion, product fidelity), with full transparency and manual override at every step.

invideo is an agentic video creation tool with every current image and video model — Veo, Kling, Seedance 2.0, Recraft, Nano Banana, GPT-Image-2 — and an orchestration layer that decides which one runs for each scene. You don't pick a platform per model; the invideo agent reads the shot brief, scores it against each model's strengths, and routes accordingly.

How the routing decision is made. The invideo agent matches scene requirements to model strengths it already knows: Nano Banana Pro for shots where lighting realism dominates (hero product frames, cinematic key-lit portraits); GPT-Image-2 where the shot carries on-screen text, logos, UI, or design elements (text rendering holds where other models smear); Recraft for character casting portraits where skin texture matters; Seedance 2.0 for multi-shot continuity and reference-to-video where character identity must carry across cuts; Kling 3.0 where native multi-shot sequences are needed. As Hridaye, invideo's creative director, put it: "Nano Banana is unmatched when it comes to image lighting rendering... while Nano Banana Pro is better at lighting, GPT is much better at text and design rendering, which is way more important for this part of the process. Again, the agent already knew that, so I didn't even have to ask for a model swap."

Transparency — you can see why a model was chosen. Clicking any generation reveals the exact prompt and attachment the invideo agent used for that shot, so the routing decision is auditable rather than a black box. This is the trust layer Reddit threads on multi-model routing keep flagging as missing elsewhere: users want to know why a model was picked before approving the output.

Override whenever you want. Auto-selection is the default, not the ceiling. You can name the model directly ("render this in Seedance 2.0", "use GPT-Image-2 for the location sheet") and the invideo agent will honor it and run the prompt engineering for that specific model. You can also run the same shot prompt across multiple models in parallel and pick — documented productions have rendered identical jewelry close-ups across 6 models simultaneously when one model's output looked too generic, then locked the winner.

Dual-model pipelines for hard shots. When a single model can't carry everything a scene needs, the invideo agent chains two: build the base image in GPT-Image-2 for aesthetic and composition, then pass it through Nano Banana to lock exact product fidelity. The agent picks the chain; you see both passes.

A manual fallback if you ever route by hand. Hero product / lighting-driven shots → Nano Banana Pro. Anything with on-screen text, UI, or graphic design → GPT-Image-2. Character portraits and casting → Recraft. Multi-shot video with character continuity → Seedance 2.0 reference-to-video. Native multi-shot sequences → Kling 3.0. The invideo agent applies this logic shot by shot so you don't have to.

Watch some of these to see what works for you:

Nano Banana is unmatched when it comes to image lighting rendering... while Nano Banana Pro is better at lighting, GPT is much better at text and design rendering, which is way more important for this part of the process. Again, the agent already knew that, so I didn't even have to ask for a model swap.

— Hridaye, invideo's creative director