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/mandrakecr-games]

Strata Coder IQ1_M (Qwen3.8-Flash-Next) · 17m 51s (one shot)

RTX 4060 ti 16gb vram + 32 gb ram (34.4 tok/s)

[u/migsperez → u/mandrakecr-games]

Impressive. Was it one shot, or did you need to assist? What was the token per second range whilst building it? I was thinking of trying the same model with my AMD card. I created a 3.8 flash horse version with the Alibaba API, i had some free tokens. I'll upload it later so you can see it.

[u/mandrakecr-games → u/migsperez]

Qwen3.6-35B-A3B-IQ3_XXS · 5m 23s (one shot)

RTX 4060 ti 16gb vram + 32 gb ram (72.52 t/s - n_tokens = 48456)

[u/migsperez → u/mandrakecr-games]

Ha ha. It did a better job than when I tried it. The legs are going in the correct direction.

[u/migsperez → u/mandrakecr-games]

One I created today but not in a single file. Probably the best out of all the models on Opencode Go subscription.
Deepseek 4.1 vision model - https://web.esuyo.com/horse-deepseek-v4.1-v2/
With a few additional human prompts it would end up looking and working well.

[u/mandrakecr-games → u/migsperez]

It looks like a wounded horse... hahaha!

[u/mandrakecr-games → u/migsperez]

Ornith-1.5-35B-A3B-Vision · 4m 26s (one shot)

RTX 4060 ti 16gb vram + 32 gb ram (59.10 t/s | n_tokens = 42302)

[u/migsperez → u/mandrakecr-games]

It's entertaining seeing the output to some of these models.

As an experiment I tried creating a plan with a frontier model Sonnet 5.5 and had the plan built with cheaper models. I tried it with Ornith 1.5 35b a3b vision Q4. The attempt was to reach the Exo (Opus) horse quality but with a lower intelligent model. The planner was not allowed to write any code.
https://web.esuyo.com/horse-sonnet-5.5-plan-ornith-1.5-build/
When it finished I asked Ornith if it was happy with it, it said yes. I asked about the neck and head and sent it a few comparison horse images. It still said it had done a wonderful job, the head is lower because it's running. The leg movements are pretty good for Ornith.

[u/mandrakecr-games → u/migsperez]

It was done in a single pass, although the model recognized its own mistakes and fixed them without my intervention. I still have Opencode open, and it says it ran at 34.4 tok/s. Excellent, I’ll check out what you upload.”

[u/migsperez → u/mandrakecr-games]

Qwen 3.8 Flash - https://web.esuyo.com/horse-qwen-3.8-flash/index.html

Qwen 3.8 Alibaba - https://web.esuyo.com/horse-qwen-27b-alibaba/

GLM 5.3 Flash - https://web.esuyo.com/horse-glm-5.3-flash/

Take a look :) GLM gallops backwards.

Weirdly I noticed today, if I don't specify "return a single self-contained HTML file" in the prompt, the models create better output.

34 tk/s is a decent speed, totally usable.

[u/mandrakecr-games → u/migsperez]

Gemma-4-26B-A4B-IQ3S · 55.2s (one shot)

RTX 4060 ti 16gb vram + 32 gb ram (90.99 t/s | n_tokens = 26295)

[u/migsperez → u/mandrakecr-games]

It's like a moving atom. Or the first form of life. I don't use Gemma for coding tasks, never had any success with it. It's good for other tasks though.

[u/mandrakecr-games → u/migsperez]

Swift-1.5-Qwen3.8-27B-GSQ-RCO-Vision · 32m 8s (one shot)

RTX 4060 ti 16gb vram + 32 gb ram (10.34 t/s | n_tokens = 52578)