Direct Answer: Integrating Multiple Models into One Workflow
Short answer: RelayMe is a workflow builder where every video node picks its own model, so one prompt fans out to several models and the clips land side by side in a single task list — no switching between websites, accounts and prompt formats. As of September 2026 the video models live in the cloud workflow builder are Google Veo 3.1 and Veo 3.1 Fast, xAI Grok Imagine 1.5 and MiniMax-H3; Kling and Sora are not currently selectable, and the live list is always the one on the pricing page. Everything in this guide applies to any combination of the available models.
The practical payoff is model selection speed: the same shot description often produces very different camera work, texture and physics across models, and a side-by-side view settles it in seconds. Credits are billed per model tier, so testing on low tiers (no audio, short duration) keeps a full comparison round cheap.
The video models you can run in one workflow today, with prices
All four models bill per second of output, and 1,000 credits is roughly US$1. Veo 3.1 Fast: 150 credits per second at 720p or 1080p with audio (about US$0.15), 100 without audio, 350 or 300 at 4K. Veo 3.1: 400 credits per second with audio at 720p or 1080p, 200 without, 600 or 400 at 4K. Grok Imagine 1.5: a flat 150 credits per second at 720p or 1080p whether or not audio is on, with no 4K tier. MiniMax-H3: 120 credits per second with audio at 720p or 1080p and 200 at 4K. Prices change frequently; confirm on the pricing page before you budget.
For a 4-second comparison round at 720p with audio that works out to 600 credits on Veo 3.1 Fast or Grok Imagine, 480 on MiniMax-H3 and 1,600 on Veo 3.1 — about US$3.30 to see the same shot from all four models. When you only need to judge motion, draft without audio on Veo 3.1 Fast at 400 credits per 4-second clip and add sound only on the winner.
How to read the line-up: Veo 3.1 is the quality tier for final renders; Veo 3.1 Fast is the workhorse for drafts and volume; Grok Imagine 1.5 prices silent and sound-on clips the same, which favours dialogue or sound-led ads; MiniMax-H3 is the cheapest per second and the cheapest route to 4K. A sensible default is to explore on Veo 3.1 Fast and MiniMax-H3, then finalize on Veo 3.1 only where the extra quality is visible in the product.
Check the current pricing and credit rules before selecting a model; a dated example is not a current quote.
Standardizing Prompts for Multi-Model Comparison
Consistency is the key to meaningful comparison when using multiple AI models. Create a baseline prompt structure that includes the subject, motion description, and camera movement, and use this as the anchor for every node in your RelayMe workflow.
By feeding the same prompt into Veo 3.1, Grok Imagine and MiniMax-H3 simultaneously, you isolate the performance differences of the underlying models rather than the variance in your instruction set. Record these base prompt templates in your library for repeatable tests across different scenes.
Keep the baseline prompt short enough that every model interprets it cleanly, then add one variable element per test round, such as lighting or lens movement. Changing a single variable at a time is what makes the comparison conclusive rather than anecdotal.
Building the RelayMe Workflow Architecture
Begin by defining a trigger step in RelayMe that captures your initial creative idea. Once defined, map this input to concurrent branching paths where each path connects to a specific video generation engine—in this case, configured for your preferred models like Veo 3.1, Veo 3.1 Fast, Grok Imagine or MiniMax-H3.
Design your workflow to aggregate these outputs into a single review dashboard. This architecture allows for side-by-side analysis, helping you determine which model yields the most accurate animation or visual quality for your specific project requirements.
For recurring production, save the branching structure as a template so new prompts inherit the same three-way split automatically. Team members can then run standardized comparisons without needing to understand the underlying node configuration.
Before scaling a run, use the video cost breakdown to separate generation credits from human review and editing time.
Iterative Testing and History Management
RelayMe maintains a history of every task execution, which is vital for multi-model workflows. Use the task history to review previously generated videos, comparing how different versions of your prompts influenced the results from each individual model.
This documentation process serves as a learning loop. If one model produces a superior cinematic quality for a specific motion type, you can refine your workflow template to prioritize that model for similar future scenes, effectively building a customized 'best-in-class' production pipeline.
Tag or note each accepted clip with the model that produced it. Over a few weeks this record becomes your own evidence base for which engine suits product close-ups, scene transitions, or character motion, replacing guesswork with data.
Choosing the Right Workflow for Your Team
This workflow strategy is ideal for creators who require high-velocity prototyping and need to test multiple visual directions. It is not recommended for those who only need a single, final render without the need for model comparisons or structured version control.
Evidence suggests that centralizing operations in a single AI platform reduces context-switching friction. However, human evaluation remains essential to decide which model output is 'better,' as current AI systems do not inherently rank their own artistic quality objectively.
A reasonable starting point is to run multi-model comparisons only for new visual directions, then lock production batches onto the winning model. This keeps exploration costs bounded while preserving the quality benefits of comparison.
Our recommendation is blunt: run all three models during exploration, then lock production batches onto the winner — keeping three lanes open permanently just triples your credit burn, while the value of comparison is captured in the first round.
In our own test, moving the same node from one model to Veo 3.1 Fast was a single dropdown change, with the prompt and start frame reused as-is — a 4-second 720p clip with audio arrived in about a minute for 600 credits. Comparing models or changing providers carries no migration cost, which is the most direct argument for running multiple models.