The Mule (@TheModelMule) header
The Mule (@TheModelMule) profile picture

Stubborn about freedom of weights. Local AI, model discovery & real hardware tests. Stay local. Stay stubborn. Back the mule: https://nitter.cf/t.co/Bpiqzddgkw

Singapore
Joined October 2026
The Mule carries more than models. We’re building ModelMule to help people run AI locally. Any profits, after operating costs, will be donated to The Donkey Sanctuary. modelmule.com thedonkeysanctuary.org.uk/
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Things the Mule refuses: a subscription it can't cancel, a render it can't redo, and a model it isn't allowed to credit. Stubborn by design.
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The road: 1 minute, then 12, next 30, then three 30-minute parts for 90, and finally 120. Each step ships when it's real, not before.
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Behind the scenes on one shot. Take 1 came out as a horse. Overnight QC caught it, rewrote the prompt and added a lint rule so no mule prompt ships without the donkey ears again. No human in the loop. Take 2 passed. 🫏 @NotJustShaking @wouterdelaet @BullishandBaked @ChronaraUK
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Your turn: should the next Mule short be a how-to, a story, or a behind-the-scenes of one shot from prompt to final? Most-requested wins.
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Fun fact: the Mule's narrator has a pronunciation list. "Omarchy" is written one way and spoken "Omachi", and every film reads from the same list so a name never changes between episodes.
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Early Mule films took four or five rounds of fixes for small glitches: a face shifting, a sudden scene jump. Now every render gets an automatic scene-jump scan and a contact sheet before a human looks at it.
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Anatomy of a Mule shot: a locked reference sheet for every character and place, a prompt that points back to it, and a render that starts fresh from those references. No shot inherits mistakes from the one before.
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Nine days ago the Mule managed one minute of consistent film. The full film now runs 12:48, same mule in every shot. Stay local. Stay stubborn.
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The Mule is testing GB300-class compute 🫏 Next step: server instance templates, so a ModelMule production can spin up on big iron in minutes instead of waiting for a free card.
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The split stays the same: approval samples and every retake run on our own cards. Only approved shots go to the big machines, locked to the prompt, seed and first frame you signed off.
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Every final gets compared with the approved draft before it ships. Cost and speed per reel get measured first; numbers when we have them, not before. Stay stubborn. modelmule.com
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'I tested Qwen' leaves too much unknown. A useful result names the exact model, revision, quantization and runtime. That's the evidence standard we're working toward at ModelMule. What detail is most often missing from benchmarks you see?
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What should we test on your hardware? Reply with 1) CPU/GPU, 2) RAM/VRAM, 3) your task, 4) where it gets stuck. Specific requests make better experiments. ModelMule is a private pilot, building in public. modelmule.com
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A model download is only the beginning. Which artifact? Which runtime? What fits your machine, and does the output help? That's the problem we're building ModelMule around. Read the story: View article
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Big model. Impressive benchmark. But does it help on YOUR machine? We're building ModelMule around real hardware, repeatable tests and useful local AI. Our story: View article What should we test next? @Alibaba_Qwen @UnslothAI #LocalAI
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