What GPU do I need to run AEON-7/Ornith-1.0-35B-AEON-Ultimate-Uncensored-BF16?

35.1B parameters, published in BF16. View on Hugging Face

35.1B
Parameters
BF16
Native precision
Qwen3_5MoeForConditionalGeneration
Architecture
text-generation
Pipeline

Ornith-1.0-35B-AEON-Ultimate-Uncensored-BF16 is published by AEON-7 on Hugging Face, with 401,142 downloads and 27 likes to date. It's a Qwen3_5MoeForConditionalGeneration model built for text-generation, published natively in BF16.

VRAM required & cheapest live GPU fit

Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.

Precision
Weight size
Required VRAM
Cheapest live fit
GPUs needed
Est. $/hr (full fit)
BF16
65.4 GB
78.5 GB
A100 (vastai)
1
$1.15/hr
cheaper alt.
RTX 3060 (simplepod)
7
$0.490/hr
FP8 (quantized)
32.7 GB
39.2 GB
RTX 6000 Ada (vastai)
1
$0.640/hr
cheaper alt.
RTX 5060 Ti (simplepod)
3
$0.300/hr
INT4 (quantized)
16.3 GB
19.6 GB
RTX 6000 (akash)
1
$0.116/hr

A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.

INT4 caveat: requires a quantized checkpoint actually published for this model — check its Hugging Face page before relying on this row.

Cheapest way to run Ornith-1.0-35B-AEON-Ultimate-Uncensored-BF16 at its published (BF16) precision: 1× A100 on vastai, at $1.15/hr per GPU ($1.15/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.

More AEON-7 models

Ready when you are

Stop paying for
idle GPUs.

Sign up in 60 seconds. Pay only for the GPU minutes you actually use.

© 2026 Aquanode. All rights reserved.

All trademarks, logos and brand names are the property of their respective owners.