Compare/Figma AI Make Prototype vs Runway Gen-4 Turbo

AI tool comparison

Figma AI Make Prototype vs Runway Gen-4 Turbo

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

F

Design & Creative

Figma AI Make Prototype

Turn static Figma frames into deployable web apps with one click

Ship

75%

Panel ship

Community

Free

Entry

Figma's Make Prototype feature uses AI to convert static design frames into interactive, deployable web apps with real data bindings. It bridges the handoff gap between design and engineering by generating functional frontend code directly from Figma designs. The feature lives inside the existing Figma workflow, requiring no context switching to go from mockup to working prototype.

R

Design & Creative

Runway Gen-4 Turbo

Real-time AI video generation at 60fps with scene-consistent output

Ship

100%

Panel ship

Community

Paid

Entry

Runway's Gen-4 Turbo is a video generation model that produces output at up to 60 frames per second in real time, with improved character and scene consistency across generations. It's available to all Runway subscribers through both the web platform and the API, making it accessible for creative workflows and programmatic integrations alike. The model represents a step-change in generation speed without the usual fidelity trade-offs that plagued earlier turbo-class models.

Decision
Figma AI Make Prototype
Runway Gen-4 Turbo
Panel verdict
Ship · 3 ship / 1 skip
Ship · 4 ship / 0 skip
Community
No community votes yet
No community votes yet
Pricing
Included with Figma Professional ($16/mo) and Organization ($45/mo) plans; not available on free tier
Included with Runway subscriptions: Standard $15/mo, Pro $35/mo, Unlimited $95/mo / API usage-based pricing
Best for
Turn static Figma frames into deployable web apps with one click
Real-time AI video generation at 60fps with scene-consistent output
Category
Design & Creative
Design & Creative

Reviewer scorecard

Builder
74/100 · ship

The primitive here is code generation from a design IR — Figma's internal node tree is surprisingly information-dense, and using it as the source of truth for code gen is a smarter bet than screenshot-to-code approaches. The DX bet is 'zero config by default, escape hatch for the real engineer' — which is the right call. My concern is the 'real data bindings' claim: if that means hardcoded JSON stubs dressed up as dynamic bindings, the moment a developer inherits this output and tries to wire a real API, the abstraction collapses. The weekend alternative here is v0 or Lovable fed a screenshot — Make Prototype earns its keep only if the generated code doesn't require a full rewrite, and that depends entirely on what the output actually looks like under the hood.

72/100 · ship

The primitive is a video generation inference endpoint that hits generation speeds fast enough to close the feedback loop for interactive or near-real-time applications, which is genuinely a different capability class than batch video generation. The DX bet is that the API surface stays consistent with existing Runway API conventions, so existing integrations get the speed upgrade without schema changes — that's the right call, and it means this isn't a forced migration. The weekend alternative test is interesting here: you cannot replicate 60fps coherent video generation with a Lambda and three API calls, the compute infrastructure is the actual product, so this passes the 'is it a wrapper?' check cleanly. My gripe is documentation: the blog post announcement doesn't link directly to updated API reference with generation parameters for the turbo model, and hunting for model IDs in a changelog is exactly the kind of friction that burns developer trust on day one.

Designer
82/100 · ship

This is the first AI feature Figma has shipped that doesn't feel bolted on — it lives at the natural end of the design workflow rather than interrupting it, which suggests the team actually mapped the job before building the feature. The interaction model is sound: designers already think in frames, and treating a frame as a deployable unit respects that mental model instead of asking them to learn a new one. My only structural concern is error states — when the AI misinterprets a component's intent, does the designer get a diff they can understand, or a black-box regeneration? That editing surface will determine whether this is a workflow tool or a demo.

No panel take
Skeptic
55/100 · skip

The category here is design-to-code, and the direct competitors are Anima, Locofy, and Builder.io — all of which have been promising 'pixel-perfect production code' for three years and consistently delivering 'good enough for a demo.' Figma's distribution advantage is real, but distribution doesn't fix the core problem: design files are rarely production-ready, and the gap between what a designer draws and what an engineer needs to ship is 80% business logic, not layout. This breaks the moment a design has conditional states, authenticated routes, or anything beyond a marketing page. What kills this in 12 months: GitHub Copilot and Cursor already accept screenshots and design tokens; Figma's moat is the file format, not the AI, and that's a thin moat once export formats standardize.

78/100 · ship

The specific claim here is real-time at 60fps with consistent fidelity, and unlike most 'turbo' model announcements that trade quality for speed and hope you don't notice, Gen-4 Turbo appears to genuinely hold scene coherence better than its predecessor — the character consistency problem that plagued Gen-3 was a real workflow killer, and this addresses it. The scenario where this breaks is long-form narrative video with complex multi-character interactions; two minutes of coherent output is not the same as a five-minute short, and anyone expecting to replace a production pipeline will hit that wall fast. What kills this in 12 months is Sora or Veo shipping a comparable speed tier natively into tools creators already live in — Runway's moat is technical lead time, and that clock is running.

PM
78/100 · ship

The job-to-be-done is precise: 'I want stakeholders to experience the design as a working thing, not a click-through prototype' — and Make Prototype nails that job without asking the user to learn a new tool. Onboarding is zero-friction by design since it's a feature inside a product people already have open. The completeness question is where it gets interesting: if this produces a shareable URL with real interactions and data, it replaces InVision, Framer, and ProtoPie for most use cases in one move — but if the output is a Figma mirror that can't be exported or hosted independently, it's a better demo tool, not a workflow replacement. The specific product decision that earns the ship is the same one that made Figma win the first time: making the collaboration artifact and the working artifact the same file.

No panel take
Creator
No panel take
84/100 · ship

The output I've seen from Gen-4 Turbo has a notable reduction in the temporal smearing and character drift that made earlier Runway generations frustrating to actually use in a project — faces hold across cuts, environments stay coherent, and the 60fps smoothness doesn't introduce the uncanny soap-opera effect I feared. The taste layer is still delegated heavily to the prompt, which means skilled prompters get great results and everyone else gets competent-but-generic, but the editing surface via the web platform lets you iterate with reference images and scene locks in a way that actually mirrors how a director thinks. The fingerprint is still there if you look — certain motion curves and lighting transitions read as distinctly Runway — but it's subtle enough that it won't embarrass you in a client deliverable.

Futurist
No panel take
81/100 · ship

The thesis Gen-4 Turbo is betting on: by 2027, video generation speed will be the primary bottleneck preventing AI video from entering real-time interactive contexts — games, live broadcast, adaptive advertising, and on-device previewing — and whoever owns the latency floor owns the infrastructure layer for those applications. The second-order effect that matters isn't faster content creation; it's that real-time generation enables a new class of product where video is generated in response to user behavior rather than authored in advance, which shifts creative power from studios to developers and interactive experience designers. The dependency that has to hold is that model quality at turbo speeds continues to improve rather than plateauing — if 60fps is achievable but 60fps-with-director-level-control isn't, the interactive use case stalls. Runway is riding the inference efficiency trend and is currently early enough to build workflow lock-in before the hyperscalers catch up, but the window is measured in quarters, not years.

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