# I Gave GPT-6 Astra Blender for Three Days. Here Is What It Built and What It Cost. > Frank Lloyd Wright's Fallingwater, my own office, and a product page for a $20,000 robot. Three builds, 54 hours of unattended Blender, and the token receipts for all of it. By Pat Simmons · September 9, 2026 · 11 min Canonical: https://www.aiformortals.co/blog/gpt-6-astra-blender-fallingwater I gave GPT-6 Astra control of Blender, the free 3D modelling software, and asked it to build three things: a flythrough of Frank Lloyd Wright's Fallingwater, the room I am sitting in right now, and a 3D model of the NEO humanoid robot embedded in a web page. You do not need to know how to code or anything about Blender to do this. Neither do I. The setup takes five minutes; the three builds took 54 hours of unattended compute and $1,771.61 in tokens. Below are the prompts, the results, and everything that broke. ▶▶0:00 / 0:001×◂⛶ _Ten camera positions, 106 seconds, rendered from the saved Blender scene. Nothing in this video is photographed._ ## Get the skill The skill below drove Blender for all three builds. Everything else on this page is linked where it comes up: all three prompts are in copyable cards, and the three finished builds are Fallingwater, the studio, and the NEO page. blender-production The skill that drove Blender for all three builds. Get the skill I did not write this prompt. I riffed at Astra for about a minute, told it to research first and produce a PRD, and this is what came back. It is 37,000 characters. The research pass alone pulled 15 measured drawing sheets and 49 interior and exterior photographs from the Library of Congress. That is the reason this works. A photograph tells a model what a house looks like. A measured drawing tells it the living space is 48 feet by 33 feet 8 inches. Most of the document's length goes on removing choices before the model can make them badly: which source wins when two disagree, which photographs to exclude, which datum each building measures from. ## Fallingwater: what it did on its own It ran for one day, five hours, eleven minutes and three seconds, without stopping, on the $200-a-month plan. I never hit a usage limit. The things it did unprompted are the story. It used computer vision on its own screen to check its work, catching things like a furniture mismatch in the guest room where the model had an upholstered seat and the reference had a writing desk and chair. It went and looked up photographs of Canadian hemlock so the trees outside would be the right species. It found a photographer's Fallingwater interior shots that were not in its own research pack, decided the pack was incomplete, and pulled them in. It also cheated, and said so by doing it. It pulled assets from Poly Haven rather than modelling every object from scratch. It did not ask permission; it worked out that the shot needed them. The finished scene holds 5,755 objects across 27 rooms, from the wine cellar up to the third-floor study. A fresh Blender process reopened the file, registered the controls, and found all 49 external image paths present. ## Where Fallingwater falls short Watch the tour and you can see it. These are the defects I would tell you to expect if you run this yourself. Rendering artifacts. Grainy speckle through several shots and a visible flicker between frames. My RAM was getting hammered, so the viewport playback was glitchy on top of that. Water. The waterfall does not read as water. It is the least convincing surface in the build. It degrades toward the end. The first rooms are excellent. The last ones are sparse, with blown-out highlights and much less detail, because I told it to wrap up. Left alone it would still be going. Camera work. The tour cuts between rooms and some angles are odd. It does not walk one continuous route, and the lower stair still reports nine wall contacts up to 42 mm. Frame rate. The brief asked for 30 FPS at 1080p. Measured performance ran 6.7 FPS with water animating to 30 FPS with it paused. It missed the gate. The project's defect register has 45 entries and four are resolved. The agent wrote its own KNOWN_LIMITATIONS.md saying the acceptance gates were not met, which is more useful than a build that claims to be finished. ## Who would actually pay for this However cool that is, the fair question is whether it is useful. Real estate, architecture, construction, interior design and developers are the obvious ones. If you are in any of those, or sell into them, this is a client deliverable. The version I would actually run: go to Zillow, find homes listed for sale, contact the broker or developer, and offer them a 3D render of the property for a few hundred dollars. People pay thousands for this. You can undercut everyone because Astra is doing the work, and you can do it at volume, because broker emails are right there on the listing. Point Astra at the listing photos and tell it to recreate them in Blender. That is a riff, not a business plan. The point is that the output is a thing somebody already buys. ## Build two: my own studio **The studio prompt** ``` # Recreate a real room in Blender A reusable prompt for turning a room video, photographs, and measurements into a detailed Blender reconstruction. Replace the bracketed fields with your own information. You can start with the video and provide measurements as you go. --- I want you to recreate my **[room type: office, studio, living room, etc.]** in Blender using the video and photographs I provide. The video may move around irregularly, revisit the same areas, and show different objects from different angles. Use those overlapping views to understand how the entire space fits together. My goal is a measured, editable model with photographic realism. At first glance, a finished render should look like a photograph of this particular room. Match the actual furniture, finishes, flooring, rugs, plants, equipment, and lighting—not just the general style. ## My inputs - Reference video and photographs: **[attach files or identify the project folder]** - Room length, width, and ceiling height: **[measurements, or “to follow”]** - Window, door, and recess measurements: **[measurements, or “to follow”]** - Furniture measurements or exact product references: **[optional]** - Presentation: **[exactly as photographed / keep the furnishings and remove temporary clutter]** - Lighting: **[match the references / describe a different lighting setup]** ## First, research the space Start with a research pass. Do not begin constructing the room yet. Extract useful video frames and assemble contact sheets with timestamps. Include wide views of each wall, connecting corners, floor and ceiling views, and closer views of important furniture and materials. Keep the original reference files intact. Check whether the footage covers the whole room. Tell me specifically what is missing or obscured. Ask for targeted additional photographs when they would resolve a gap; do not automatically request another complete room tour. Use the overlapping views to establish the layout. Do not force a seamless panorama if camera movement would distort the relationships between nearby furniture and distant walls. Create an inventory of the room's architecture, furnishings, fixtures, and visible materials. Separate what you can observe from what you are estimating. Do not treat an assumed furniture brand, standard door size, or ceiling tile size as a confirmed measurement. Account for camera perspective, wide-angle distortion, and exposure differences. If the source is HDR, make consistently converted viewing copies before judging colors and lighting. Do not mistake the camera's processing for the material's true color. Write a PRD and build plan containing: 1. The intended result and scope. 2. The reference inventory and coverage gaps. 3. Confirmed measurements, estimates, and unresolved questions. 4. The furniture and material inventory. 5. The modeling, lighting, and camera-matching approach. 6. The build stages, review criteria, and final deliverables. Finish this first phase by showing me the contact sheets, the plan, and the most useful next measurements. Wait for me to start the reconstruction phase. ## Keep measurements consistent Use one coordinate system and a consistent real-world scale. Preserve my original measurement units alongside any conversions. Clarify where each measurement starts and ends. Distinguish the main wall face from a window recess, the opening from its trim, and the finished floor from the top of a rug. Do not add the same recess or trim depth twice. Record unknown values as unknown. A precise-looking number is not useful if it was invented. Use measured geometry and multiple reference views together rather than stretching the room to fit a single photograph. ## When I ask you to build Create a dedicated Blender project with separate files and checkpoints. If another Blender project is running, use an isolated process and verify the target file before making changes. Do not overwrite, close, or redirect an unrelated session. Evaluate the available Blender MCP tools and Blender Python workflow. Choose the appropriate control method for each operation; neither replaces careful modeling or visual verification. Check which instance an MCP connection controls before using it. Build and verify the measured room envelope first: walls, floor, ceiling, openings, recesses, trim, and major furniture positions. Then finish one representative area to establish the required material and lighting quality before applying that approach throughout the room. The finished scene must include recognizable, detailed objects. Model the features that affect shape and shadows: furniture legs and supports, cushion seams, cabinet gaps, handles, rug edges, window frames, and plant leaves. Use subtle, correctly scaled surface detail for wood grain, fabric, paint, and other finishes. No final placeholder furniture, swollen cushions, featureless plant blobs, or generic textures that erase the room's identity. Do not hide unfinished modeling behind heavy blur, dramatic grading, or a single favorable camera angle. Reproduce the observed light sources, their direction, relative brightness, color, and shadow softness. Keep material color separate from colored light falling on it. Use Cycles for the final photographic renders, with quality settings chosen through inspected results rather than an arbitrary sample count. If I requested a tidied room, record what was removed. Preserve working equipment and plausible cable connections. Do not silently redesign the room or replace its furniture. ## Verify and deliver Compare renders with reference frames using matched camera angles. Inspect every wall direction and important close-up. Check dimensions, furniture placement, floor contacts, reflections, material scale, and lighting. Review the actual rendered images, repair visible discrepancies, and reopen the saved project to verify that it works and its assets are available. Deliver an editable Blender file, dimensioned room drawings, photographic stills from several useful viewpoints, and a brief account of remaining uncertainty. Keep reference comparisons separate from presentation images where deliberate cleanup changes the scene. Aim for photographic fidelity without claiming that a handheld video establishes exact hidden geometry or guarantees literal pixel-for-pixel identity. ## Handle references privately Do not publish the project or send private reference media to an additional external service without my instruction. For outputs intended for public sharing, flag visible personal information and use neutral replacements for sensitive screen content, documents, or labels. Keep private reference files separate from the shareable deliverables. --- **Sharing note:** This template does not require sharing your source footage, exact room measurements, or project files publicly. If you choose to share your own media, review both visible content and embedded metadata, including location information. ``` This one is relevant to more people, because everyone has a room they work in. I shot a blurry 360 video of my studio on my phone, took the measurements, and handed over both. I hit my usage limit halfway through this build. It is the only one of the three where that happened, and it is worth knowing before you start: a long Blender run can outlast your plan's window. Astra noticed the video was HDR and washed out, and made properly tone-mapped reference frames before judging any colours. Then it built a contact sheet out of video stills to get a sense of the space. It asked whether to keep the clutter — boxes, cables, water jugs — and I told it to remove the temporary stuff. The first pass was blobby and cartoonish and I said so. It asked what keyboard, mouse and Stream Deck I use; I told it to look at the video and identify the actual products, and to look up product photos where the video was too grainy. That is the single most useful instruction in this whole post. At three hours and thirty-seven minutes it was giving itself notes like "moving the console about 11cm forward improves all three lounge views while keeping it grounded." The detail it reached from a low-res phone video is the part I did not expect. The coffee maker. The disinfectant wipes. My Cafe Garibay coffee. The teleprompter, the bamboo, the Google Home, the Polaroid, the 3D camera on the floor. The book on the shelf is Ogilvy on Advertising, and it read the spine. It modelled the mesh of the chair. It even mocked up what was on my monitor at the time. The console is where it spent its time and it shows. Set the render next to the real thing and it is nearly identical. Other surfaces stay boxy, because I had it rush them. It also produced measured drawings, which I did not ask for. Orthographic projections straight off the geometry, dimensioned in metric and feet-inches, each dimension labelled either measured or estimated. That distinction is what makes them usable: it tells you which numbers you can drill to. _Wall A. The 4.5212 m span and the 2.9972 m ceiling are tape measurements. The window recess profile is marked unmeasured._ _Floor plan, projected from the same geometry._ The full set is at pat-studio-astra.vercel.app. The reason I built it: I want to hang floating shelves and lights on the back wall, and I can now ask what they look like from my actual camera position before I drill anything. ▶▶0:00 / 0:001×◂⛶ _36 seconds through the reconstructed studio. Cycles stills, 3,765 objects, 1.38 million polygons._ ## Build three: a robot on a web page **The NEO prompt** ``` # Build a premium 3D NEO robot experience Act as a product designer, reference researcher, Blender artist, and frontend engineer. Create a faithful, premium redesign study of the official 1X NEO page: https://www.1x.tech/neo. Treat this as a client-style design exercise. The central improvement is a complete, interactive 3D robot in a softly lit studio, followed by an engaging scroll experience using the brand's existing visual language and real product footage. Build the robot first and show me the actual 3D result before integrating the marketing website. ## Available references and setup If the accompanying NEO starter kit is present, read `README.md`, open `REFERENCE_INDEX.html`, and inspect `research/ROBOT.md`, `research/BRAND.md`, `research/BLENDER.md`, `assets/manifest.json`, and `assets/video-manifest.json`. All paths are relative to the extracted kit. The images, screenshots, and video frames are references from the official website; they are not generated robot renders. Keep them intact and write your new work to separate folders. This project must work without access to the creator's computer, earlier projects, generated models, renders, special skills, or paid generation services. Inspect the tools actually available. Use Blender's Python API (`bpy`) for reproducible modeling, rendering, and export. Use a Blender MCP connection for live inspection if available; otherwise use an isolated Blender process and saved Python scripts. If Blender is missing, finish the research and PRD, then explain the specific installation needed. Never present a reference photograph as the 3D deliverable. If the kit is missing, start from the official product and order pages, https://www.1x.tech/neo and https://www.1x.tech/order. Collect your own references from those pages and their linked official sources. Do not assume that a file named in this prompt exists. Record original URLs and retrieval dates. Public source URLs can change. Do not use similarly named domains as substitutes for 1X. ## Phase 1 — Research and PRD Inspect the full official page on desktop and mobile. Study the logo, navigation and its scroll states, typography, spacing, rounded media panels, glass play controls, CTAs, icons, product copy, and closing studio portrait. Inspect pixels as well as DOM/CSS. Distinguish measured source details from proposed changes. Build a multi-view robot reference board covering the face, profile, full body, shoulders, textile construction, hands, shoes, ear rings, and any usable rear views. Compare the Tan, Gray, and Dark Brown order images, targeting the Tan campaign exterior. Use video frames to resolve details. Do not mix exposed engineering hand imagery with the finished campaign appearance without explaining why. Write `PRD.md` with the intended experience, model deliverables, source inventory, interaction plan, implementation approach, milestone acceptance criteria, performance targets, and remaining uncertainty. Make practical implementation decisions and continue into the robot milestone. ## Phase 2 — Complete robot and studio Create a source-faithful, fully three-dimensional Tan NEO in Blender. The primary silhouette reference in the kit is `assets/images/order-neo-body-96a45b2e.webp`; the face is `assets/images/order-neo-face-c9e24d8e.webp`; the profile is `assets/images/order-neo-cc3c7adf.webp`; the shoe reference is `assets/images/order-neos-boots-192c3ddc.webp`. The intended studio mood is `assets/images/neo-gamma-2102d301.webp`, the closing image from the product page. Its old CMS label is not a reliable product-generation identifier. Match the elongated soft head, two physical camera lenses and bezels, oval illuminated ear perimeters, neck separation, shoulders, torso and pelvis proportions, diagonal chest/abdomen textile regions, ribbing, seams, cuffs, articulated five-finger hands, ankle hems, and knit shoes with distinct soles. Use the published height, approximately 1.6764 metres, for overall scale; document other dimensions as estimates. Match large shapes before spending time on fine texture. Model the back, sides, underside, palms, feet, and gaps between limbs. Reference coverage is incomplete: there is no validated clean rear campaign view in the supplied set. Some introduction-film frames that appear useful at first are actually front views. Inspect every claimed view. Document inferred geometry and keep it visually plausible. Avoid invented sci-fi details. Use a neutral studio with broad soft light, restrained highlights, a gentle floor shadow, and a quiet pale background. Recreate the closing portrait's lower-body opacity fade in presentation while keeping the underlying model complete. Provide a separate inspection view with the fade disabled. The original fade is embedded in the source image's alpha channel. Maintain an editable Blender master and a reproducible script workflow. Keep source observations separate from modeling estimates. Fit and compare front, side, and three-quarter silhouettes under simple shading before refining fabric, lenses, lights, and materials. Review actual renders and correct visible errors; an inventory of modeled parts is not evidence of likeness. Export a GLB that preserves the intended appearance in a browser. Bake unsupported procedural material effects into portable PBR maps as needed. Check normals, UVs, texture color spaces, scale, transparency, and material roughness after export. Reopen the saved Blender file in a fresh process and inspect the exported GLB independently. Present the editable `.blend`, the `.glb`, a freely rotatable browser viewer, a complete 360-degree orbit, and front/profile/back/three-quarter comparison images. Include a concise uncertainty and remaining-quality report. A photograph, generated illustration, billboard, image sequence, or generic primitive mannequin does not satisfy this milestone. Pause for my review here before marketing-page integration. ## Phase 3 — Website after model review Use the approved robot as the first thing visitors see. Preserve 1X's quiet, warm, premium tone. The September 2026 reference measurements are a starting point: page `#f7f7f7`, ink `rgba(0,0,0,.72)`, dark logo `#41403c`, media corners 80px desktop / 48px mobile, pill buttons, and glass controls using white at 16% opacity with 24px backdrop blur. Major headings are approximately 56px desktop / 30px mobile; body text 24px / 16px. Refer to `assets/brand/tokens.json` and the screenshots for context rather than imposing fixed widths on every screen. Use the original SVG logo and icons from the kit. The source font is ABC Diatype. Font binaries are not included: use a properly licensed copy if supplied, or a clean system sans fallback and state that substitution. Rebuild clean components; do not ship captured analytics or copy the original app's hidden markup. Design a scroll-controlled studio sequence with a smooth complete robot rotation and a few deliberate pauses or camera moves for the face, hands, textile, and feet. Start with one sticky canvas and a normalized scroll timeline; roughly four viewport heights is a candidate desktop length, to be tuned in the browser. Keep native scrolling and avoid trapping the user. The first frame must already look composed and intentional. Transition into large, rounded panels showing original product demonstrations, with restrained feature callouts, accessible glass playback controls, and purposeful connections between the robot and footage. Source video links and observations are in `assets/video-manifest.json`; do not assume local MP4 files are supplied. Use native HLS where supported, a compatible player where necessary, or a verified local derivative with provenance. Preserve captions and review crops on mobile. Start playback muted when automatic; provide pause, mute, and explicit play controls. Call out only supported product features. Treat performance and capability claims as manufacturer statements. Clearly distinguish expert-assisted operation from autonomous behavior; a demonstration clip alone does not prove autonomy. Recheck time-sensitive specifications, pricing, availability, and order links before writing them into the page. React, TypeScript, Three.js / React Three Fiber, and GSAP ScrollTrigger are a reasonable default, but adapt to the existing project. Keep one renderer, resize it correctly, pause work offscreen, and use a responsive render budget. Aim for a compressed model around 8 MB on desktop and 4 MB on mobile if achievable without sacrificing likeness. These are targets to measure, not promises. Lazy-load video and secondary media. Provide keyboard-accessible navigation and media controls, visible focus states, sufficient contrast, and a useful `prefers-reduced-motion` mode. Include a matching loading poster, a clear load-error fallback, touch-friendly model inspection, and a mobile experience that remains useful without long pinned motion. Use official outbound order links; this prototype does not need payment collection. ## Delivery and verification Deliver the research/PRD, editable model, modeling scripts, browser export, inspection viewer, final website source, and concise run instructions. Keep references, generated work, and optimized runtime assets in separate folders. Track source URLs and inference notes. This educational reference kit does not confer a commercial media or font license; obtain appropriate assets and permissions for a production release. Verify the saved master, exported model, full rotation, resemblance from multiple angles, desktop/mobile layout, playback, links, keyboard use, reduced motion, and actual loading behavior. Report what was tested and any remaining limitations honestly. Deliver a working local project; publish the finished redesign only if I ask. ``` The last build is for anyone with a website. A real 3D object on a page is one of the fastest ways to make a site read premium, and it is where web design is going. I pointed Astra at the 1X NEO product page — a $20,000 home robot — and asked it to extract the branding, the logo, the rounded corners, the glassmorphism CTAs, the icons, then build a 3D model of the robot and make it the hero. Research agent, PRD, fresh build agent, same as the others. It ran twenty hours and twenty-two minutes overnight and produced 69 iterations. The revision history runs 2:22am, 3am, 4am, 4:43am, revision 50, and on until the afternoon. Twenty hours is hard to justify for one object when Fallingwater was an entire house room by room. _The finished page. Orbit the robot and scroll the story, or open it full screen._ The model itself is very good. The mesh, the texture, the shoes, the face, the hands built from separate reference photos, the charging port on the back. Zoom in and there is a studio reflection in the surface. The one thing it missed is the shell colour: NEO is cream and the model drifted white, and it was closing the gap when I stopped it. The page is a build demo, not 1X's site. ## What the three cost Cache reads dominate every row. A long agentic run re-reads its own growing context on every turn, so 1.19 billion of the 1.22 billion input-side tokens are the model reading back what it had already done. BuildWall clockInputCache readsOutputCostFallingwater1 d 5 h 11 m10,314,143465,753,2162,108,208$674.31The studio3 h 37 m10,559,353443,879,9362,105,972$654.77NEO product page21 h 15 m7,064,070285,310,5921,731,504$442.53Total~54 h27,937,5661,194,943,7445,945,684$1,771.61 These are API-equivalent costs, which means token counts priced at published rates. All three ran on the $200-a-month plan, so no invoice for $1,771.61 exists. Fallingwater and NEO never hit a limit. The studio did, halfway through. The rate is not constant. Fallingwater burned $674 over 29 hours; the studio spent nearly the same money in three and a half. Cost tracks how hard the model is working, not how long it is left running.