Photoreal 3D capture for design & creativity workflows
Luma AI is a NeRF-based 3D capture and editing platform that converts phone photos and video into photoreal 3D models and interactive viewers. It’s best for designers, VFX artists, and creators who need high-fidelity, web-shareable 3D assets without building photogrammetry pipelines. Pricing mixes a usable free tier with paid Pro and Team plans for heavier export and private-storage needs.
Luma AI is a Design & Creativity tool that converts photos and video into photoreal 3D scenes using NeRF-style rendering and cloud processing. Its primary capability is producing editable, relightable 3D captures from a smartphone sweep or camera turntable, with exports to common 3D formats and a web viewer. Luma’s key differentiator is a cloud-first pipeline that generates high-quality neural 3D from ordinary footage rather than requiring dense photogrammetry rigs. It serves concept artists, AR/VR teams, and product designers. Pricing is accessible: a free tier exists plus paid Pro and Team plans for larger projects and private hosting.
Luma AI is a cloud-native 3D capture and neural rendering platform focused on turning standard photos and smartphone video into photoreal 3D assets. Originating from a startup focused on NeRF (neural radiance field) workflows, Luma positions itself at the intersection of photogrammetry and neural rendering: it offers automated scene reconstruction without manual camera-calibration steps. The platform emphasizes an easy capture-to-share loop with a mobile capture workflow, cloud processing, and an embeddable web viewer. Luma’s value proposition is enabling designers and creators to produce interactive 3D content quickly for product visualization, AR previews, and virtual production.
Luma’s core features reflect its NeRF-first approach. The Capture + Cloud pipeline ingests an iPhone/Android video or a sequence of photos and returns a neural 3D scene with free-viewpoint navigation. Exports support glTF/GLB and USDZ for downstream AR and DCC workflows. The web viewer provides relighting toggles, adjustable exposure, and a smooth orbit camera for embedding or sharing links. Luma also offers integrations/plugins for DCC tools (export-friendly formats) and basic material extraction so textures and approximate PBR maps can be used in Blender or game engines. Projects can be marked private or shared with a link.
Pricing mixes a free tier and paid plans (approximate current pricing listed; check luma.ai for latest). The free tier allows limited uploads/processing and public viewer links suitable for testing or small portfolio captures. Pro is a monthly subscription (approx. $15/month) that removes public-only restrictions, increases concurrent render quotas, and unlocks higher-resolution exports and private projects. Team or Enterprise options provide multi-seat billing, higher cloud-credit allowances, priority processing, and custom SLAs for studios and commercial use. Enterprise is quoted per account with custom storage and on-premise options discussed with sales.
Luma is used by a range of creatives and technical roles: concept artists use it to create photoreal environment proxies for lookdev, and AR developers convert product photography into USDZ assets for mobile demos. For example, a Product Designer using Luma can produce web-viewable 3D product previews that reduce photo shoot costs, while a VFX Lookdev Artist uses it to generate HDR-backed environment references. Compared to alternatives like Polycam, Luma emphasizes NeRF-based relight and free-viewpoint rendering rather than dense mesh photogrammetry alone.
Three capabilities that set Luma AI apart from its nearest competitors.
Current tiers and what you get at each price point. Verified against the vendor's pricing page.
| Plan | Price | What you get | Best for |
|---|---|---|---|
| Free | Free | Limited uploads/processing, public viewer links, low-res exports | Individual testers and hobbyist capture |
| Pro | Approx. $15/month | Higher-resolution exports, private projects, increased render quota | Freelancers and creators needing private exports |
| Team | Approx. $49+/seat/month | Multi-seat billing, larger cloud-credit pools, team management | Small studios and AR/VR teams |
| Enterprise | Custom | Custom SLAs, dedicated quotas, billing and storage options | Large studios and production houses |
Copy these into Luma AI as-is. Each targets a different high-value workflow.
Role: Luma AI assistant tasked with converting a single smartphone sweep into a production-ready USDZ for web preview. Constraints: Accept one 20–45s handheld sweep (60–120 frames) shot on neutral background; auto-align and denoise, preserve PBR material channels (baseColor, roughness, metallic, normal); final file size <= 50 MB and viewable in Luma web viewer. Output format: Provide a single USDZ file, a 1280x720 JPG thumbnail, and a short viewer share link. Example input: 30s clockwise sweep around a sneaker at chest height, diffuse overcast lighting.
Role: Luma AI assistant producing an HDR environment proxy from a short exterior/interior video for use as lighting reference in VFX. Constraints: Input is a 30–60s 360° or 180° handheld sweep including a chrome and gray sphere for reference; preserve high-dynamic range, minimize sky clipping, fill missing panorama areas using sky extrapolation heuristics. Output format: 16-bit EXR equirectangular HDRI (4096px width minimum) plus a low-poly environment mesh with baked irradiance maps and a JSON metadata file listing capture time, exposure stops, and reference sphere positions. Example: 40s plaza sweep containing chrome ball and gray card on a tripod.
Role: Luma AI engineer optimizing a NeRF-derived capture for mobile AR deployment. Constraints: Target mobile platforms (iOS/Android): final .glb must be under 25 MB, polycount budget <= 60k, textures capped at 1024 px, include metallic-roughness workflow and tangent-space normals; generate three LODs (100%, 50%, 25%) and embed collision bounds. Output format: Single .glb file with LODs, separate manifest JSON listing polycounts, texture sizes, and recommended runtime scale, plus a base64 small preview image (512px). Example: Consumer headphone product, texture atlas used to reduce file I/O.
Role: Luma AI technical artist producing a photoreal 3D capture of transparent/translucent objects (e.g., perfume bottle). Constraints: Input: two sweeps—one with dark background and one with bright background; use polarizer metadata if available; separate retouching must produce a transmission (alpha) map, roughness map, and corrected normal map; minimize ghosting and interior refraction errors. Output format: USDZ and textured mesh (PLY) plus a ZIP with baseColor, transmission, roughness, normal maps (2048px max) and a short capture log. Example: A 40s clockwise sweep with white and black backdrop passes.
Role: Senior VFX lookdev artist guiding Luma AI to create production-ready environment proxies for lighting virtual assets in a shot. Step 1 Capture Guidance: request 2–3 sweeps including bracketed exposures (±2 stops) and reference chrome/gray spheres; log focal length and camera motion. Step 2 Processing: merge exposure brackets for HDR, generate 8k EXR equirectangular, reconstruct proxy geometry as Alembic with per-face irradiance, and produce a relightable HDR light card set. Step 3 Deliverables & Metadata: 8k EXR, Alembic proxy, orientation/scale transforms, ACES/OETF notes and a short QC checklist. Few-shot examples: (1) 35mm handheld 60s plaza sweep -> 8k EXR + abc; (2) 24mm dutch-angle interior 45s sweep -> interior HDRI + proxy.
Role: Digital conservator using Luma AI to create a museum-grade archival NeRF capture for conservation and research. Step 1 Capture Plan: recommend multi-scale capture—wide context sweep, mid-range rotational passes, and high-resolution stills of key details; include color chart and a metric scale bar visible in first frame. Step 2 Processing Settings: enable high-detail reconstruction (no mesh decimation), preserve 16-bit color, prioritize texture fidelity over file size, perform geometric cleanup but keep provenance layers for audit. Step 3 Deliverables: high-density PLY, OBJ+MTL, 8k texture maps, QC report with per-surface accuracy estimates and capture metadata. Example: small marble statue vs mural capture notes.
Choose Luma AI over Polycam if you prioritize NeRF-style relighting and embeddable web viewers rather than dense mesh photogrammetry.
Head-to-head comparisons between Luma AI and top alternatives: