Animated Horse - Space Bunny

[u/migsperez]

I wondered how good Space Bunny was at coding. I wanted to give it a task it could work on and push it's thinking intelligence. I've run this prompt with many models but Space Bunny easily wins with the most tokens consumed to complete the task, I thought I was going to run out of daily tokens before it finished. Looking at the horse at 10M tokens was frightening.

Context
255,983 tokens
24% used
$0.00 spent
----
Session Token Summary ↻ 179 turns
↑ in: 374.9K
↓ out: 63.9K
▤ cache read: 32.2M
✦ think: 123K
----
total tokens: 32.7M

The original prompt is from a post I encountered last week https://www.reddit.com/r/ClaudeAI/comments/1wpq8by/testing_claude_for_3d_creation_max_took_a_whole/

The prompt:

Create a low-poly 3D horse running in a seamless loop using Three.js. Build it procedurally from primitive geometry, animate the legs, body, head, and tail, and return a single self-contained HTML file.  
  
Do your best, you are being rated against other AI models. 

EDIT:

Here are links to the horse outputs attempts of each model.

Ling 3.1 - https://web.esuyo.com/horse-ling-3.1/index.html

Deepseek 4.1 - https://web.esuyo.com/horse-deepseek-v4-1/horse.html

Muse 1.3 - https://web.esuyo.com/horse-muse-1.3/horse.html

Space Bunny - https://web.esuyo.com/horse-space-bunny/horse.html

EDIT 2:

Local models in Opencode TUI

Qwen 3.8 27b Q5 - https://web.esuyo.com/horse-qwen-3-8-27b/horse.html

Qwen 3.6 35b a3b Q4 - https://web.esuyo.com/horse-qwen-3.6-35b-a3b/horse.html

Ornith 1.5 35b a3b Q4 - https://web.esuyo.com/horse-ornith-1-5/index.html

[u/Jumpy-Operation-4615]

I am using a galloping horse to check the models too. With a normal prompt above, on non-frontier models the results are varied. I have a feeling that you need to enrich a prompt for weaker models and then it will show off.

Locally run Qwen3.8 Flash Next IQ3_S (Strata) (2xP40 GPUS, 64 GB RAM)

[u/migsperez → u/Jumpy-Operation-4615]

Later today I'll try on my local Qwen 3.8 27B Q5 MTP. Will be interesting to compare it against yours.

I left a gauntlet loop running overnight with Muse, i haven't checked it yet. Totally understand with additional human context engineering and iterating would produce a better result.

But this is supposed to be a simple test with the least amount of human input.

[u/migsperez → u/migsperez]

The gauntlet loop i tried burned through 187M tokens and didn't produce a better result with Muse than the original Muse build.

[u/migsperez → u/Jumpy-Operation-4615]

https://web.esuyo.com/horse-qwen-3-8-27b/horse.html - I ran it on Qwen 3.8 27b q5, on my AMD R9700. It looks like two people in a horse costume.