--- title: "Luma vs Weave" description: "Compare Luma vs Weave in 2026. Discover differences in AI video generation, workflows, creative control, and production tools for marketing teams." canonical: "https://lumalabs.ai/news/luma-vs-weave" source: "https://lumalabs.ai/news/luma-vs-weave.md" --- # Luma vs Weave _By Luma team ยท July 17, 2026_ When an agency needs to deliver a product launch film by Friday, the choice of creative tools shapes whether the team makes it or misses it. [Luma AI](https://lumalabs.ai/ray3-2) and Figma Weave represent two distinct approaches to AI-assisted creative work. Luma builds proprietary models designed for production-grade campaigns. Weave aggregates access to fifty-plus AI models through a node-based canvas. The difference shows up in the edit bay: one platform gives creative directors frame-level control over the final film, while the other gives teams a menu of model options to connect together. For agencies finishing ad campaigns and production studios, color grading launch films, that distinction matters. ## **Key Takeaways** - Luma builds proprietary models like [Ray 3.2](https://lumalabs.ai/ray3-2) with up to 16 keyframes in a single clip, while Weave aggregates access to 50+ external AI models through a node-based interface - Luma's 16-bit EXR exports in ACES2065-1 color space drop directly into professional post-production, while Weave's outputs depend on which model you select - Creative teams working on brand campaigns often choose Luma for its [AI Agents](https://lumalabs.ai/agents-guide) that maintain context from brief to final delivery - Luma's 8-face simultaneous tracking handles ensemble scenes that production teams need for automotive spots and retail campaigns - Both platforms serve professional teams, but Luma focuses on finishing the campaign, while Weave focuses on connecting different models ## **How Each Platform Approaches Creative Work** Luma builds its own models. The company's [Ray 3.2](https://lumalabs.ai/ray3-2) video generation model, Uni-1 image system, and [AI Agents](https://lumalabs.ai/agents-guide) all come from Luma's research. When an agency uses Luma, they're working with tools designed from the ground up to finish campaigns. The company serves over 30 million registered users globally. Major agencies, including Serviceplan, Dentsu, and Publicis Groupe, have built their creative AI work around the platform. Mazda runs brand campaigns through it. Weave takes a different path. The platform, [acquired by Figma](https://www.calcalistech.com/ctechnews/article/byyrqlbjwg) for over $200 million in October 2025, connects users to models from multiple providers. An agency working in Weave can access Runway, Flux, Google Veo, Kling, and others through a single interface. The node-based canvas lets teams build visual chains connecting different AI tools. Rather than developing its own models, Weave functions as an aggregator that brings competing models under one roof. The philosophy shows up in how each platform handles a typical project. Luma keeps the campaign context from the first brainstorm through final delivery. Weave gives teams the flexibility to switch between model providers mid-project. [Try Luma Now](https://auth.lumalabs.ai/sign-up) ## **What Each Platform Actually Does** ### **Luma's Core Capabilities** #### **Ray 3.2 Video Generation** The [Ray 3.2 model](https://lumalabs.ai/ray3-2) turns text, images, and existing footage into a finished video. Creative directors control the output through: - Up to 16 keyframes in a single clip for scene-by-scene direction - 16-bit EXR export in ACES2065-1 for color grading and VFX work - 8-face simultaneous tracking for ensemble scenes - Draft mode for quick preview before committing to final renders - Video-to-video modification that preserves performance while changing the scene #### **AI Agents** [Luma Agents](https://lumalabs.ai/agents-guide) stay with the project from brief to final cut. They brainstorm concepts, generate assets across video, image, and audio, then revise based on feedback. The same agent that helped develop the initial creative direction remembers that context when the client requests changes two weeks later. #### **Skills** [Skills](https://lumalabs.ai/news/luma-skills) let teams save processes they repeat. A team that regularly turns product photography into hero shots can build that process once and run it on every new product. Campaign briefs become social variants through the same saved approach. ### **Weave's Core Capabilities** #### **Multi-Model Access** Weave connects teams to over 50 AI models through a single subscription. The platform includes video models, image generators, and 3D tools from multiple providers. Teams can access Runway, Flux, Veo, Sora, Kling, and Luma's Ray 2 all in the same project. #### **Node-Based Canvas** The visual canvas lets teams connect AI operations into chains. An image generation node can feed into a video node, which passes to an upscaling node. Teams can save and share these chains across projects. #### **Team Collaboration** Weave includes shared credit pools, workspace sharing, and team management. Multiple people can work from the same credit budget with unified billing. ## **Features Side by Side** ![table-img](https://cdn.sanity.io/images/2ylxvaa2/production/b080e80be55464dbec258c1562fb385a31989570-482x692.jpg) ## **Who Uses Each Platform** ### **Luma's Core Users** Luma serves professional creative teams working on: - **Advertising agencies** building campaign assets across video, image, and audio - **Brand teams** producing product launches, retail content, and social variants - **Production studios** creating pre-visualization, VFX elements, and finished films - **Enterprise creative departments** that need brand consistency across all generated assets The platform's partnerships with Publicis Groupe, Dentsu, and Serviceplan reflect this focus. These agencies use Luma to produce client work, not to experiment with AI for its own sake. ### **Weave's Core Users** Weave targets teams that want to: - **Test multiple AI models** before committing to one provider - **Build visual chains** connecting different tools in sequence - **Manage team access** through shared credit pools - **Budget transparently** with published per-model costs ## **When Creative Teams Choose Luma** ### **The Launch Film Scenario** A brand needs a product launch film in two weeks. The creative director has storyboards. The product exists as CAD files and photography. The deadline is fixed. With Luma, the team uploads reference images to [Ray 3.2](https://lumalabs.ai/ray3-2) and uses the multi-keyframe system to define shot progressions. Each keyframe represents a story beat. The model interpolates between them. The EXR exports go straight to the colorist. The edit happens in Premiere. The film delivers on time. With Weave, the team selects a video model from the menu, connects it to their preferred image upscaler through nodes, and generates clips. They might test three different models before finding the output quality they need. The node canvas helps them build a repeatable chain. The timeline extends while they evaluate options. ### **The Ensemble Scene** An automotive spot needs six people walking through a showroom. Expressions matter. Body language sells the scene. Luma's 8-face simultaneous tracking handles the ensemble. The model maintains consistent performance across all six people throughout the shot. Motion stays natural. Faces stay expressive. Weave's output depends on which model the team selects. Some handle single faces well. Group dynamics vary by provider. ### **The Brand Campaign** A retail client needs thirty localized assets by Tuesday. Same creative direction, different markets, consistent brand look. Luma's [Skills](https://lumalabs.ai/news/luma-skills) let the team build the first asset, then run the same approach across all thirty variants. The [AI Agent](https://lumalabs.ai/agents-guide) remembers the brand guidelines from the original brief. The client gets consistent work across every market. Weave's node chains can handle repetition, but brand consistency depends on careful prompt engineering for each model in the chain. ## **Post-Production Integration** The edit bay reveals platform differences clearly. ### **Luma's Handoff** When a Luma clip finishes rendering, the editor receives: - [16-bit EXR files](https://lumalabs.ai/news/introducing-ray-3-2) in ACES2065-1 color space - HDR-ready footage that matches professional camera sources - Files that drop directly into DaVinci Resolve, Premiere, or AVID - Consistent output quality from a single proprietary model The colorist starts the grade immediately. The VFX artist composites without conversion. The final delivery matches the rest of the project. ### **Weave's Handoff** Weave's output varies by model selection. Some models export at web resolution. Others handle higher quality. The team needs to test their chosen model's export capabilities before committing to a project timeline. Generation speed varies across models in the platform. For teams already working in Premiere or Resolve, the handoff question determines which platform fits their existing process. ## **The Multi-Model Question** Weave's fifty-plus model access raises an interesting question: do creative teams benefit from model variety? ### **Arguments for Model Variety** - Different models excel at different styles - Teams can compare outputs before committing - No vendor lock-in to a single provider - New models become available through the same subscription ### **Arguments for Specialized Depth** - Consistent output quality across all projects - Features designed to work together (keyframes, tracking, EXR export) - [AI Agents](https://lumalabs.ai/agents-guide) that maintain context throughout the project - Brand intelligence that understands style at the model level For agencies working on deadline, the consistency argument often wins. Testing models takes time. Learning model-specific prompting takes longer. When the campaign needs to ship on Friday, a team that knows Luma's [Ray 3.2](https://lumalabs.ai/ray3-2) deeply outpaces a team still evaluating options. ## **Enterprise Considerations** Large agencies evaluating both platforms consider: ### **Luma's Enterprise Approach** - [Custom agreements](https://lumalabs.ai/enterprise) scaled to campaign volume - Partnerships with global agency networks including Publicis Groupe - [International offices](https://lumalabs.ai/news/luma-ai-opens-for-international-business-with-former-wpp-executive-jason-day-leading-new-london-office) for regional support - Training and onboarding for creative teams - API access for custom integrations ### **Weave's Enterprise Approach** - Custom credits and training - Slack-based support - API keys for development work - Unified billing across team members The Figma acquisition suggests Weave will eventually connect to Figma's design tools, potentially offering workflow advantages for teams already in that ecosystem. That integration hasn't shipped yet. ## **Where the Platforms Head Next** Luma continues expanding its proprietary model capabilities. Recent updates to [Ray 3.2](https://lumalabs.ai/news/introducing-ray-3-2) added the multi-keyframe system and HDR exports. The company's research spans creative AI and physical AI, suggesting future capabilities beyond current video and image generation. Weave's Figma acquisition points toward design tool integration. Teams using Figma for design work may eventually see Weave's AI capabilities appear within their existing creative tools. That connection remains future roadmap rather than current feature. For creative teams choosing today, the question centers on what the work requires. Campaign production with fixed deadlines and post-production handoffs favors Luma's specialized depth. Exploratory work testing different AI approaches favors Weave's model variety. The director finishing Friday's launch film cares about 16-keyframe control and EXR exports. The team experimenting with AI styles cares about access to fifty models. Both are valid creative needs. The platforms serve them differently. ## **Final Verdict** **Choose Luma** if your team delivers production-grade campaigns on fixed deadlines. The platform's proprietary [Ray 3.2 model](https://lumalabs.ai/ray3-2) with 16-keyframe control, professional EXR exports, and 8-face tracking gives creative directors the precision they need to finish client work. [AI Agents](https://lumalabs.ai/agents-guide) maintain brand context from brief to delivery, while [Skills](https://lumalabs.ai/news/luma-skills) make repetitive workflows efficient. For agencies at Publicis Groupe, Dentsu, and Serviceplan building campaigns for clients like Mazda, Luma's specialized depth wins when the film ships Friday. **The deciding factor:** Campaign teams working in Premiere and DaVinci Resolve typically choose Luma for its post-production integration and consistent output. Experimental teams building proof-of-concepts typically choose Weave for its model variety and visual workflow builder. Both serve professional creative work. The difference is whether your Friday deadline requires finishing the campaign or exploring possibilities. [Try Luma Now](https://auth.lumalabs.ai/sign-up) ## **Frequently Asked Questions** ### **What specific features make Luma's Ray 3.2 different from the video models available in Weave?** Ray 3.2 includes up to 16 keyframes in a single clip, letting creative directors define shot progression frame by frame. The model also offers 16-bit EXR export in ACES2065-1 color space, which drops directly into professional color grading. Weave provides access to multiple video models, but their specific capabilities vary by provider. Luma built Ray 3.2 specifically for campaign production, while Weave aggregates models built for various purposes. ### **Can agencies use both Luma and Weave on the same project?** Yes. Weave includes access to Luma's Ray 2 model through its platform. Some teams use Weave for early exploration across multiple models, then move to Luma's direct platform for final production when they need [Ray 3.2's features](https://lumalabs.ai/ray3-2) like multi-keyframe control and HDR exports. The platforms serve different stages of the creative process. ### **How do Luma's AI Agents differ from Weave's node-based approach?** [Luma Agents](https://lumalabs.ai/agents-guide) maintain project context from brief to final delivery. They brainstorm, generate, and revise while remembering previous decisions and brand guidelines. Weave's node-based canvas connects AI operations visually but doesn't maintain context between sessions in the same way. For campaign work where brand consistency matters across multiple rounds of revision, Luma's agent approach keeps the creative direction coherent. ### **How do the platforms handle brand consistency across multiple assets?** Luma's Uni-1 system provides model-level brand understanding. The AI learns brand style, character references, and visual guidelines, then maintains that understanding across all generated assets. [Skills](https://lumalabs.ai/news/luma-skills) let teams save and repeat successful approaches. Weave's consistency depends on careful prompt engineering for each model in the chain. Teams generating thirty localized variants often find Luma's built-in brand intelligence reduces manual correction work. ### **What post-production formats does each platform support?** Luma's Ray 3.2 exports [16-bit EXR files](https://lumalabs.ai/news/introducing-ray-3-2) in ACES2065-1 color space, the standard for professional color grading and VFX work. These files integrate directly with DaVinci Resolve, Premiere Pro, and AVID without conversion. Weave's export options depend on which model you select. Some models in the platform export at web resolution while others support higher quality. Production teams should verify export capabilities for their chosen Weave model before committing to a project timeline.