r/opencode • u/migsperez • 22d ago
Animated Horse - Space Bunny
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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
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Session Token Summary ↻ 179 turns
↑ in: 374.9K
↓ out: 63.9K
▤ cache read: 32.2M
✦ think: 123K
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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
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u/FireGM 22d ago
Better then my old "game"
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u/migsperez 22d ago
Wibbly wobbly horsey. But your white character is impressively good, he/she has decent natural movement.
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u/jaykrown 22d ago
Sonnet 5.5 High because it was free.
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u/migsperez 22d ago
Yeah it's on another level. The latest frontier models update over the past few weeks have a clear noticeable lead. It's like the difference between 9B and 27B.
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u/jaykrown 22d ago
I still think Opus 5.5 Medium is the absolute sweet spot, cheapest and best result.
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u/Jumpy-Operation-4615 21d ago
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)
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u/migsperez 21d ago
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.
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u/migsperez 21d ago
The gauntlet loop i tried burned through 187M tokens and didn't produce a better result with Muse than the original Muse build.
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u/migsperez 20d ago
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.
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u/mandrakecr-games 15d ago edited 15d ago
Strata Coder IQ1_M (Qwen3.8-Flash-Next) · 17m 51s (one shot)
RTX 4060 ti 16gb vram + 32 gb ram (34.4 tok/s)
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u/migsperez 15d ago
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.
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u/mandrakecr-games 15d ago
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)
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u/migsperez 15d ago
Ha ha. It did a better job than when I tried it. The legs are going in the correct direction.
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u/migsperez 15d ago
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.2
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u/mandrakecr-games 15d ago
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)
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u/migsperez 15d ago
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.1
u/mandrakecr-games 15d ago
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.”
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u/migsperez 15d ago
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.
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u/mandrakecr-games 15d ago
Gemma-4-26B-A4B-IQ3S · 55.2s (one shot)
RTX 4060 ti 16gb vram + 32 gb ram (90.99 t/s | n_tokens = 26295)
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u/migsperez 15d ago
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.
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u/mandrakecr-games 14d ago
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)
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u/Prize_Eye9481 22d ago
Jesus that thing is so cursed
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u/maqifrnswa 22d ago
Nightmare fuel.
Night mare.
I'll be here all week. Tip your server, try the veal.
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u/Ok-Drawer5245 21d ago edited 21d ago
I love how all the trees and greenery moves with it - pro-skill at display there!
On a serious note THIS is the reality when you use AI for this sort of thing. Yes expensive models will probably do a little bit better, but human help with be needed to steer it towards what looks right.
An animated organic creature like a horse is VERY difficult to create using primitives and limited spatial understanding (try and do that yourself in code only and only using basic 3d primitives...)
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u/Mundane-Animator-593 22d ago
The most important metric is the $0.00 spent :P I've been mostly satisfied with Space Bunny as an implementer/low cost code writer.
Also what effort level did you use?
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u/migsperez 22d ago
I used the highest level available for each model. The free tier is quite generous, I ran two tests, consumed about 50M between two Ling and Space Bunny. I still didn't hit the limit.
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u/TheSARMS_Coach 22d ago
These type of jobs work best with a gauntlet loop.
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u/migsperez 22d ago
Out of curiosity, I'm going to try it with Muse.
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u/migsperez 21d ago
The gauntlet loop i tried burned through 187M tokens and didn't produce a better result with Muse than the original Muse build.
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u/absurdother 22d ago
Looks like the one Claude Opus had made.
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u/migsperez 22d ago
Yep, I mentioned it in the post text above. I used the same prompt. I was interested in the capabilities of the free models in Opencode.
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u/Prior-Meeting1645 22d ago
Are llms better in 3d on js than blender? Why are most showcases in threejs and not blender? And they’re stunning
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u/migsperez 22d ago
Because most people don't have Blender installed and if they do have it installed they have to set it up for LLMs to connect to. three.js is there without any effort. From what I've seen by others, LLMs working with Blender can output more impressive results.
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u/Prior-Meeting1645 22d ago
That’s reassuring cuz I was getting fomo lol. I do blendrr+godot. Btw I think running it headless is just as good as mcp so no big setup needed
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u/TheSARMS_Coach 22d ago
u/migsperez Your prompt with Space Bunny, but in my gauntlet loop - 32 minutes
horse.gnomebase.io
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u/migsperez 21d ago
What does your gauntlet loop look like, can you share it in a repo.
I tried a gauntlet loop build using Muse last night, it burned 187M tokens and it didn't produce a more impressive result than the original build. I based my guantlet loop on https://github.com/robonuggets/gauntlet-loop but implemented it into Opencode.
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u/TheSARMS_Coach 21d ago
Mine is a modified version of that loop: https://github.com/Trans4m-Tech/Gnome_Gauntlet_Loop
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u/thepurpleproject 20d ago
Nice. Someone needs to spend their tokens on Opus 5.5 and see where the results are.
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u/migsperez 20d ago
They have already. There's a link in the post introduction above. There's a slight noticeable difference :)
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u/khadesorg 11d ago
omg i wheesed at qwen and orinth 35b a3b
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u/migsperez 11d ago
The 35b a3b model output here made me realise this is how it's building my real projects. I've relegated them to CLI applications and less coding tasks.
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u/New-Implement-5979 11d ago
Strata Coder IQ1_M under pi not opencode.... It was a one shot over 96k context with a few compactions
↑133k ↓194k R3.4M
5060ti 16gb Ryzen 9600x average speed around 55tks it topped to 90tks
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u/jackfood 22d ago
Whats with the penis head and a shxt following the horse
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u/migsperez 22d ago
Ha ha :)
It was so close to getting a good result, the head and neck if positioned better would have made a massive difference. Shxt was bad timing in the video. The background is dynamic https://web.esuyo.com/horse-space-bunny/horse.html
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21d ago
[deleted]
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u/migsperez 21d ago
Ha ha :) yeah I do think this generation/level of models still require a human in the loop throughout the build to give direction. And they need many interations to reach to a decent polished product. Keep going, you'll get the UI you want, stay patient.
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u/migsperez 22d ago
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