Google Vertex AI alternatives for creative teams

What should a creative team use instead of Google Vertex AI?

Use a creative platform that resells the same Veo models, because almost all of them do and none of them charge more for it. Vertex is Google Cloud's model-serving infrastructure, so the video model you reach through it is the identical model you reach through Melius, Runway, Adobe Firefly, Krea or Google's own Flow, at the same published per-second rate. What changes is everything around the model: whether you need a cloud project to start, where the output lands, and how fast you can iterate.

One thing to know before you start comparing: Vertex AI isn't called that any more. At Cloud Next 2026 Google renamed the platform to Gemini Enterprise Agent Platform and Vertex AI Studio became Agent Studio. The marketing URL cloud.google.com/vertex-ai now lands on the Agent Platform product page, the model reference and Provisioned Throughput trees have moved, and the older doc paths still resolve while serving renamed content. Veo on Vertex AI is Veo on Gemini Enterprise Agent Platform. If you're evaluating it on a page that still uses the old name, check the date on the page.

What to know before you pick

• The model is the same and so is the price. fal.ai charges Google's exact list rate for Veo 3.1, $0.20 a second silent and $0.40 with audio at 1080p, with no cloud project and no bucket. So Vertex is not the cheap route, it's the same route with more setup.
• Audio doubles the cost on the flagship, and you pay for every clip the model successfully returns, usable or not. An 8-second Veo 3.1 clip at 1080p with audio is $3.20, so ten takes to land one shot is $32. Failed requests aren't charged, which is the one piece of good news in the billing model.
• Veo on Vertex runs in a single region, us-central1, and takes English prompts only. Clips are 4, 6 or 8 seconds, in 16:9 or 9:16.
• Google built Flow for exactly this reason. It's Google's own creative surface for Veo, it has a canvas, and it costs $19.99 a month, which tells you what Google thinks Vertex is for.

What separates a creative surface from an inference endpoint?

Four questions, and the first one ends the evaluation for most creative teams before quality ever comes up.

Can a creative start without a cloud project?

Read Google's own prerequisites for generating a video on the platform. You sign in to or create a Google Cloud account. You select or create a project, which needs the Project Creator role. You enable the platform API, which needs either Owner or Service Usage Admin. Then, in the console, you set an output directory by browsing to a Cloud Storage bucket you have created.

That's an account, a project, two named IAM roles and a storage bucket before the first frame exists, and a billing account on top in practice. There is a no-code interface, Media Studio, and it is a model menu plus a prompt box and four parameters: aspect ratio, number of results, video length and output directory. None of this is a criticism of the product. It's a description of infrastructure, and it's the reason a creative director can't self-serve here.

Where does the work live?

On Vertex, output goes to a `gs://` bucket. The documented flow points your generations at Cloud Storage rather than into an in-product library, and nothing in the docs describes a gallery, a version history or a comment thread. A GCP project with IAM roles is a permissions model, not a shared workspace, and finding the third take of a shot you generated last Tuesday means knowing your own bucket structure.

This is the gap the alternatives fill, and it's worth being specific about what filling it means: a canvas or a library that holds the takes, versions you can step back through, assets a teammate can find without asking you, and a link you can send to a client. Those aren't conveniences on a production, they're most of the work.

Does the throughput match how you work?

This is the finding that surprised us most, and it comes straight from Google's documentation. Veo is excluded from pay-as-you-go on the platform, so sustained capacity comes from Provisioned Throughput, which is sold in units called GSUs. The enforcement window on a reservation of 1 to 9 GSUs is 2,000 seconds.

Google's own worked example spells out what that means: with 1 GSU you can generate a four-second Veo 3 video within a few minutes, and then you can't generate another of the same size until the window ends. Do the division and a 2,000-second window is one four-second clip with audio roughly every 33 minutes, because audio burns the allowance at twice the rate of picture. Getting to one clip a minute means the 60-second window, which the table only grants at 67 GSUs or more.

Creative iteration doesn't work at one take per half hour. It works in bursts of ten or twenty variations while an idea is still warm, which is what a per-second on-demand endpoint gives you and what a reserved-capacity window does not.

What do you give up in governance?

Honestly, quite a lot, and this is where Vertex earns its place. Veo on the platform supports data residency, customer-managed encryption keys, VPC Service Controls and Access Transparency. Google contractually commits not to use your data to train or tune models without your instruction, across both GA and pre-GA models. Generally available Veo versions are on Google's list of indemnified generative AI services, covering both training data and generated output. And it all lands on one cloud invoice, which in a large organization can save months of procurement.

No creative platform below offers that stack. If you're at a company where legal needs an indemnity and security needs VPC Service Controls, the honest answer is that you should use the platform, and give a creative team something else for exploration.

Two caveats on the governance case, though. Zero data retention isn't the default; prompts may be logged for abuse monitoring and an exception has to be requested, and for advanced models Google's own addendum says zero retention may not be possible. And the indemnity covers generally available versions only, so Veo 3.1 Lite, still in preview, sits outside it. Veo also isn't named as a covered service in either the generative AI SLA, which covers specific Gemini inference methods, or the platform SLA, which covers training and batch prediction. If an availability guarantee matters to you, get it in writing before assuming Veo carries one.

The seven compared

Capabilities and list prices as of September 2026, from each platform's own documentation and pricing pages. Several are running sales that will have ended by the time you read this, so these are list prices. Veo access is stated as each platform documents it.

1. Melius

Melius is the Agentic OS for creative work: you describe the outcome and an agent builds the workflow, routes each step to a model and leaves every step editable. A node-based canvas sits underneath, so the pipeline is visible and re-runnable, and plenty of people drive it from Slack or the command line without opening the canvas at all.

Against Vertex the difference is what surrounds the model. Veo 3.1 sits alongside Gemini Omni Flash and Gemini Omni Flash 1.1 among roughly forty video and image models on the same subscription and the same credit pool, so comparing Veo against Kling, Wan or Seedance on one shot is a branch, not a second vendor. And the canvas is the thing Vertex has no equivalent of: the takes stay where you made them, teammates see the work live, and changing an upstream node re-runs everything below it.

What it does well

• Veo 3.1 sits alongside Gemini Omni Flash, Gemini Omni Flash 1.1, Kling, Wan and Seedance in the same library of leading models on one subscription, so per-step routing is a setting rather than a procurement exercise.
• Every canvas is real-time and collaborative by default, with presence for people and for agents, so there's no session to share or enable.
• Unlimited seats on every paid plan, which is a different shape from per-seat creative tools and from per-project IAM.
• It's reachable from Slack, the Model Context Protocol (MCP), a CLI and a REST API, so an agent you already use can drive the canvas.
• You own what you create and can use it commercially, subject to the underlying model providers' terms, and Melius does not use your work to train AI models.
• The Semantic Assets Manager, on Professional and above, searches the team library by description, not by filename, which is the thing a storage bucket cannot do.

The trade-off

Melius does not offer the governance stack, and for some buyers that settles it. There's no VPC Service Controls, no customer-managed encryption keys, no data-residency selection and no IP indemnity of the kind Google extends to generally available Veo. A regulated enterprise with a security review will find Vertex answers questions Melius does not.

The catch: the best place to work with Veo, and not the place to satisfy a procurement questionnaire.

Best for: creative teams and agencies who want Veo next to every other leading model, in a workspace where the process and the assets stay put. Current numbers are on the pricing page.

2. Google Flow

The most honest alternative to Google's infrastructure is Google's own creative product. Flow is what Google built for people who want to make things with Veo rather than serve it, and its existence is the clearest evidence that Vertex was never meant to be a creative surface.

It has an adaptable canvas, Scenebuilder, video extension, video-to-video editing, characters and avatars, and natural-language iterative editing. There's also a gallery of about a dozen featured tools, from a video resizer to a storyboard studio, which you can remix, and you can describe a new tool in plain language if you're on a paid tier. It reaches Gemini Omni and Nano Banana Pro too, not only Veo.

What it does well

• No cloud project, no IAM roles, no bucket. A consumer Google account and a subscription.
• Scenebuilder and the canvas give you somewhere for a sequence to exist instead of a folder of files.
• Natural-language iterative editing, so a note becomes a revision instead of a new prompt.
• Every tier including the free one carries 50 daily credits, with paid plans adding a monthly pool on top, so evaluating it costs nothing.
• It reaches Gemini Omni Flash, currently at the top of the blind text-to-video rankings.

The trade-off

It's Google models only, which is the whole point and also the limitation: no Kling, no Seedance, no Wan, so a shot that Veo handles badly has nowhere else to go. Flow is sold as an individual Google AI subscription with no per-seat or team tier, so credits sit with one account and two people on one project means two subscriptions. Tools can be shared and remixed, but the credit pool cannot.

Access is also conditional in ways a professional tool usually is not: 18 or over, a consumer Google account, and features that Google says may vary by subscription tier, platform and region. The visible watermark on the lower tiers is the practical blocker for client work, and removing it means the top tier.

The catch: the right creative surface for Veo, built for one person at a time.

Best for: individuals working with Google's models who want Google's own tooling and don't need a second model family or a shared workspace.

3. Flora

Flora is the closest thing to Melius in shape: an infinite creative canvas where you wire models, transforms and assets into reusable visual pipelines, with an agent that chains steps conversationally. It carries Veo 3.1 alongside Seedance, Kling and a long tail of others.

Where it leans hardest is live team editing. Real-time cursors, commenting, shared team assets and usage analytics are the product's centre of gravity, and it's priced per seat accordingly.

What it does well

• Real-time cursors and commenting directly on the canvas, so review happens where the work is.
• Shared team assets and usage analytics, which is the governance a creative lead actually wants.
• Node workflows are reusable, so a pipeline that worked becomes a template.
• An in-canvas video timeline for trimming, arranging and rendering.
• SSO on the enterprise tier, which is rare at this end of the market.

The trade-off

Pricing is per seat with metered usage on top, so the bill has two moving parts and a busy month moves both. The free plan excludes video models entirely, which means you can't evaluate the thing you came for without paying.

Flora has no model of its own either, so rights on any given clip inherit from whichever model the node called, and that's a per-node question rather than a per-platform answer.

The catch: excellent collaboration, on a bill with two variables.

Best for: small teams who want a shared canvas and are comfortable with seat-based pricing plus usage.

4. Runway

Runway is the incumbent creative video platform, and it's the one entry here with a frontier research lab of its own shipping continuously: Gen-4.5, then Aleph 2.0, Ruby, Solaris and GWM Worlds 2. Aleph 2.0 with Edit Studio also gives it the strongest editing surface in the comparison, where an instruction propagates across cuts in a multi-shot sequence instead of applying to one clip.

It also hosts other people's models, Veo 3.1 among them, plus Wan 3.0 and Seedance 2.5, and in September it shipped plugins that put its lineup inside Premiere Pro and After Effects.

What it does well

• Edit Studio is a real edit surface, taking an input video between 2 and 30 seconds at up to 1080p with no more than ten cuts.
• Its own models sit beside the third-party ones, so you can compare Gen-4.5 against Veo on the same platform.
• Ruby turns an SDR generation into true HDR and exports 16-bit EXR, which nothing else here offers.
• Brand kits and 20GB to 500GB of asset storage by tier, so the work has a home.
• The Premiere and After Effects plugins remove the round trip for anyone cutting in Adobe.

The trade-off

Runway's terms of use say inputs and outputs may be used to train and improve its models, on every plan except Enterprise. For a team working on unreleased client material that's a genuine objection, and it's the sharpest contrast with Vertex in this whole comparison, because Google's contractual position on training is the stronger one.

The credit arithmetic is also unforgiving. Gen-4.5 costs 12 credits a second, and the $15 Standard plan's 625 monthly credits buy 52 seconds of it on Runway's own published figure, so budget by the shot rather than by the month.

The catch: the best editing in the category, with the weakest training-data position.

Best for: teams who want to generate and assemble in one place and can put the work on an Enterprise plan if confidentiality matters.

5. Adobe Firefly

Adobe reaches Veo 3.1 and Veo 3.1 Fast as partner models, alongside Luma Ray3, Kling 3.0 and Runway Gen-4.5, and in September it went further than anyone else by putting generative models directly into the Premiere timeline: draw a range on a track, describe what you need, and generate without leaving the application.

Firefly Boards is the canvas, but the real argument is position. If your team already finishes in Premiere and After Effects, this is the only option on the list where the model shows up inside the tool you were going to use anyway.

What it does well

• Generation inside the Premiere timeline, with sequence settings matched automatically and the credit cost shown before you commit.
• Firefly plus partner models from Google Veo, Kling, Runway and Luma, all reachable from one picker.
• Firefly's own model is trained on licensed Adobe Stock and public domain content and never on customer work.
• Firefly Custom Models let a studio train on its own assets so generations conform to a house look.
• Entry pricing is $9.99 a month for 2,000 credits, the cheapest way onto Veo with a creative surface attached, though partner models are a premium feature that draws on that allowance.

The trade-off

The commercial-safety guarantee covers Firefly's own model only. The moment you pick Veo, Kling, Runway or Luma from that same picker you inherit their terms instead, and the interface makes them look equivalent when they aren't. Firefly's own video model is also well behind the frontier on quality, so the value is pipeline position, not output.

Credits do not roll over, which penalizes the lumpy production calendar most teams actually run, and Boards is a lighter canvas than Melius or Flora, not a workflow surface.

The catch: the best place to work, and you still have to read the terms per model.

Best for: teams already inside Creative Cloud who want the round trip gone.

6. Krea

Krea has the widest Veo coverage of anything here, carrying Veo 3, 3 Fast, 3.1, 3.1 Fast and 3.1 Lite, so if you specifically want to compare Veo variants against each other it's the most direct route. It runs Seedance and Vidu alongside them.

Its own contribution is Krea Realtime, a model that streams frames as they generate and lets you change the prompt mid-generation, which is genuinely useful for look development rather than final pixels.

What it does well

• All five current Veo variants in one place, which no other platform here matches.
• Realtime Canvas renders a sketch toward photoreal fast enough to direct interactively.
• A commercial license starts on the $9 Basic tier, which is the lowest entry to cleared output on this list.
• A free tier with 100 daily units, enough to judge the models.
• Nodes on the Pro tier for chaining steps into a repeatable workflow.

The trade-off

Two tiers are doing different jobs here and it's easy to conflate them. The $9 Basic plan is where a commercial license starts, but it carries only selected video models, and Krea says the Pro plan at $35 is what unlocks all of them, so Basic is not established as a route to Veo. Collaboration is also thin until the Business tier, where the product is described as a workspace for teams; below that it's a strong individual tool with a library.

Krea's published pricing was also difficult to read reliably, with figures differing between sources, so confirm the tier you want before committing.

The catch: the most Veo variants, the least team structure.

Best for: individuals and small teams doing model comparison and look development.

7. fal.ai

If what you actually wanted from Vertex was an API, fal is the answer, and the pricing comparison makes the argument on its own. fal charges Google's exact published rate for Veo 3.1: $0.20 a second at 720p and 1080p without audio, $0.40 with, $0.40 and $0.60 at 4K, with no minimums.

Same model, same price, no cloud project, no IAM roles, no storage bucket, no allowlist request and no reserved-capacity window. That is the whole pitch and it's a strong one.

What it does well

• Google's list price per second, so choosing it costs nothing in unit economics.
• Genuinely on-demand, with no provisioned-throughput window between takes.
• Wan, Kling and other models are behind the same API, so switching models is a parameter.
• Pay per use with no subscription, which suits irregular volume.
• A playground alongside the API, so a non-developer can at least check output.

The trade-off

It's not a creative surface and doesn't pretend to be. No canvas, no versions, no asset library, no collaboration, no brand controls. If nobody on the team writes code, this solves nothing.

You also give up the governance stack without gaining a workspace, so it's the wrong answer for the enterprise buyer who chose Vertex for VPC Service Controls and the wrong answer for the creative director who wanted somewhere to work.

The catch: it removes the cloud project and adds nothing else.

Best for: engineering-supported teams who want Veo behind their own product and never wanted a console.

When the platform is still the right answer

There's a real case for staying, and it isn't about the model. If your security review requires VPC Service Controls, customer-managed encryption keys or a data-residency commitment, no creative platform on this list will pass it. If legal requires an indemnity covering both training data and generated output, Google extends one on generally available Veo versions and the alternatives do not. If procurement is the binding constraint, putting AI spend on an existing cloud invoice can be worth more than any feature.

The mistake is treating that as one decision. Governance and iteration are different requirements with different users, and the teams handling this well buy both: the platform for anything that ships through a controlled pipeline, and a creative surface where exploration actually happens. The alternative is a creative team that files a ticket to try an idea, which is how ideas stop being tried.

So the question to ask isn't which one is better. It's which of the two problems you have, and whether the answer is the same for the person doing a security review and the person trying twenty versions of a shot before lunch.

Frequently asked questions

Run the same shot through Veo 3.1 and three other video models on one canvas, with no cloud project, no storage bucket and no capacity window between takes. Open Melius.