Gemini 4 Argon Built a Tesla Roadster in Blender From 4 Pictures

Gemini 4 Argon (Google’s model, also called Argon 4) built a white Tesla Roadster style car in Blender from 4 pictures and one prompt, then wrote a three.js launch show where the car climbs a ramp, hangs upside down and rolls back to land. The car cost about $1.54 (52 calls, 20.5 minutes) and the whole project about $6.96 (200 calls), both estimated from the measured token counts at Google’s list price. This post has the 4-step setup, the exact prompt, every follow-up prompt with my typos, and the show itself, which you can play below.

Play the launch show: kartit.net/demos/roadster-argon.

Key facts (quick answer)

Fact	Gemini 4 Argon, Roadster in Blender
Date	20 and 21 October 2026
Model	Gemini 4 Argon, medium effort (gemini-4-argon-medium)
Agent	Google Antigravity command line (agy)
Link to Blender	MCP for Blender, free add-on
Input	4 reference pictures (front, left, rear, right) + 1 prompt
The car in Blender	52 calls, 20.5 min, about $1.54
Car tokens	2.06M input (1.79M cached), 81K output
Everything, launch show included	200 calls, about $6.96
All tokens	16.3M input, 309K output
Mesh	7,420 polygons (measured in Blender)
Speed	about 4 s a step on medium, 10 to 20 s on high
Price basis	Google list price: $2/M input, $0.10/M cached, $10/M output incl. thinking

TL;DR

• 4 pictures and 1 prompt in, a 3D car in Blender out, in 20.5 minutes.
• The car cost about $1.54 for 52 calls (estimated at list price).
• The car plus a flying three.js launch show and all its fixes: about $6.96 for 200 calls.
• The finished mesh has 7,420 polygons.
• Medium effort ran about 4 s a step; high effort ran 10 to 20 s.
• The show took 11 prompts of direction; the car took 1 prompt and 1 fix.

Play the launch show

This is the actual page Argon wrote, running in your browser. Drag to orbit the camera, or pick a shot from the bar at the bottom. On a phone, turn it sideways.

What did Gemini 4 Argon build?

A 3D car in Blender that matches 4 reference pictures, then a cinematic web page around it.

Blender is a free 3D app, the kind studios use for models and animation. Argon did not click around in Blender like a person. It drove Blender through MCP, a plug that lets the AI send commands to Blender and take screenshots of its own work. The agent was Antigravity, Google’s AI coding agent, used here from the terminal (its command is agy).

The car has a white wedge body, a black lower body, a dark glass canopy, a thin white light bar at the front, a red light bar at the back and black 6-spoke wheels. The finished mesh has 7,420 polygons.

What were the 4 pictures?

Four flat views of the same car: front, left side, rear, right side. That is all Argon got to look at.

How close is the 3D car to the pictures?

Close on shape and proportions, simpler on detail. Each pair below is the reference picture on the left and Argon’s Blender model from the same angle on the right.

The body, the canopy, the light bars and the 6-spoke wheels all landed where the pictures put them. The surfaces are flatter than in the pictures and the side panels are plainer. It is not as polished as a car made by a 3D artist, but it is good enough for a game or a short film.

How do I connect Gemini 4 to Blender?

Four steps, all free tools.

1. uvx mcp-for-blender setup and type 7 to pick Antigravity only. This installs MCP for Blender, the free add-on that connects the AI to Blender.
2. Open Blender. The add-on starts its server by itself. To see it, press N and open the tab “MCP for Blender”.
3. agy mcp list should show: blender enabled.
4. agy --model gemini-4-argon-medium starts the agent on Gemini 4 Argon at medium effort.

What was the prompt?

One prompt, word for word:

Build this roadster in Blender with your Blender tools. Look at the 4 reference views first: refs/front.png, refs/left.png, refs/rear.png, refs/right.png. Start from an empty scene. White wedge body, black lower body, dark glass canopy, a thin white front light bar, a red rear light bar, black 6-spoke wheels. Check your work with viewport screenshots from the same 4 angles and fix what does not match. Finish with a nice 3/4 front view in the viewport.

The important line is the one that asks Argon to check its own screenshots from the same 4 angles. That is what made it compare its model with the pictures and fix the differences without me.

What did I ask after that?

Short follow-ups, typed fast. Here they are in order, typos included:

1. “there is some black shapes on windshield smoothen design”
2. “open this in a three js and make a cinematic rpesentation of the car”
3. “the car should have thursters that throw vapor like in bottom to elevate the car animation”
4. “too much white glow”
5. “car supposed to hve doors open like this” (with a picture)
6. The stunt, in 11 prompts. I also gave it the link to the Roadster launch video. Some of them:
   • “you need to replicate this full animation scene”
   • “review the car animation it is supposed to speed then rotate and land from the jump”
   • “it has sucktion mecanism to stay”
   • “mimic drone style filiming car when it is going up then jump rotate and land”
   • “the car supposed to stay inverted till it jumps then it has right and left thrusters to rotate it back to land”
   • “fix the animation is wrong”

Three.js is a free code library that draws 3D scenes inside a web page. Argon wrote the whole show around its Blender car: the C-ramp, the suction fan that holds the car upside down, the roll thrusters, the drone camera and the landing. One last fix round on the evening of 21 October lit the fourth act better, made the climb, hang and roll easier to read, eased the landing with a camera shake and put the doors on proper hinges.

How much did it cost?

About $1.54 for the car and about $6.96 for everything. Both are estimates: I measured the tokens of every Gemini call and priced them at Google’s list price. It is not a bill.

Part	Calls	Input tokens	Output tokens (incl. thinking)	Estimated cost
The car in Blender (20.5 min)	52	2.06M (1.79M cached)	81K	$1.54
Everything: car, launch show and all fixes	200	16.3M	309K	$6.96

Prices used for Gemini 4 Argon: $2 per million input tokens, $0.10 per million cached input tokens, $10 per million output tokens, thinking included.

Most of the car’s input was cached: 1.79M of the 2.06M tokens. Cached input is the part of the conversation the model has already seen, and it is billed at $0.10 per million instead of $2. That is why 2 million tokens of reading cost so little.

Medium or high effort?

Medium. In this recording medium effort took about 4 seconds a step. High effort took 10 to 20 seconds a step. For a build where the agent takes a screenshot, looks, and changes one thing at a time, that difference adds up fast.

Caveats

• This is one build on one day, not a benchmark. Another car or another prompt will cost more or less.
• The costs are estimates from measured token counts at list price, not an invoice.
• The car is a Roadster style model built from 4 reference pictures, not an official Tesla model.
• The launch show needed 11 prompts of direction. The car needed 1 prompt and 1 fix; the show is where the work was.

My take

What surprised me was the self-check. I asked Argon to take screenshots from the same 4 angles as my pictures and fix what did not match, and it did exactly that, round after round, while I watched. A 3D car for about $1.54 is cheap enough to try an idea before paying a 3D artist. The show was the opposite: the animation needed a director. Short, badly typed prompts were enough, as long as I said what was wrong.

Sources

• Measured token counts for every Gemini call, session of 20 and 21 October 2026, plus the fix prompt of 21 October 2026, priced at Google’s Gemini 4 Argon list price (ai.google.dev/gemini-api/docs/pricing, read 21 October 2026).
• Polygon count measured in Blender on the final model.
• MCP for Blender (free add-on): https://github.com/ahujasid/mcp-for-blender
• Playable launch show: https://www.kartit.net/demos/roadster-argon/

Independent project by Anass Kartit, kartit.net. Not affiliated with Google or Tesla.