LOADING DATASHEET
LOADING DATASHEET
by KandooAI
RANKED #43 OF 74 IMAGES · OVERALL #172 OF 6,596 · VIBE SCORE 5.9 · 289 VOICES
Juggernaut on Civitai. 213,165 downloads. Community image checkpoint.
57 mentions
24 mentions
26 weeks · 36 voices
HOLDING UP
Recent vibe is steady. No clear fade in the crowd.
Open weights. You can use a hosted service, or download it and run it yourself, free.
Open weights: download Juggernaut once and it's yours. No subscription, no rate limits, works offline.
2.6B parameters (SDXL base architecture), FP16 safetensors file is about 6.6 GB
NVIDIA GeForce RTX 3060 12GB
12 GB VRAM
~$260 USEDFP16 precision at 1024x1024, 30 steps, ~12 s/image
NVIDIA GeForce RTX 4070 Super 12GB
12 GB VRAM
~$590 NEWFP16 precision at 1024x1024, 35 steps, batching and Hi-Res fix, ~4 s/image
NVIDIA GeForce RTX 4090 24GB
24 GB VRAM
~$1750 USEDFP16 precision, rapid batches with multi-ControlNet and upscaling, ~1.5 s/image
The three cards above are researched picks. Search the machine you actually have — we only say yes if it should reply at a usable speed, not just load the weights and crawl.
HARDWARE PICKS & PRICES ARE RESEARCHED FROM THE LIVE WEB AND REFRESHED AUTOMATICALLY. TREAT THEM AS BALLPARK, NOT GOSPEL.
Everyday jobs on each of those rigs: how long Juggernaut takes, and how good the crowd says it is at that kind of work.
| THE JOB | BARE MINIMUMNVIDIA GeForce RTX 3060 12GB | SWEET SPOTNVIDIA GeForce RTX 4070 Super 12GB | FULL POWERNVIDIA GeForce RTX 4090 24GB |
|---|---|---|---|
| Make an imageone picture at normal settings | ~12 S★★★★★ | ~4 S★★★★★ | ~2 S★★★★★ |
STARS ARE THE COMMUNITY SCORE FOR THAT KIND OF WORK, DOCKED FOR HOW SQUASHED THE WEIGHTS GET AT EACH TIER. TIMES ARE COMPUTED FROM RESEARCHED SPEEDS. BALLPARK, NOT GOSPEL.
People are mostly happy with Juggernaut. Biggest praise: how results look.
201 POSTS · 88 COMMENTS · REDDIT · X · HACKER NEWS · LEMMY · GITHUB
5 thumbs up · 0 thumbs down
Checked picks first: tags say why you would switch, stars say how fully each one stands in for Juggernaut.
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SUPIR (Super Resolution) - Tutorial to run it locally with around 10-11 GB VRAM
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