Apertus-v1.5-8B Memory at each precision, the licence in plain words, and where it fits.
Short answer. Apertus-v1.5-8B needs about 6.5 GB of memory at 4-bit, 11 GB at 8-bit and 19 GB at full 16-bit precision, including runtime overhead. It has about 8.9 billion parameters. Licence in short: commercial use allowed. By memory alone, on ANVE’s launch configurations: ANVE One fits at BF16, ANVE Office fits at BF16, ANVE Office Pro (GPU) fits at BF16. These are estimates from its published size, not benchmarks.
01
What it is
Apertus-v1.5-8B is a vision-language model: it reads images (scanned pages, photos, charts and screenshots) as well as text, published by the Swiss AI Initiative (EPFL and ETH Zurich) on Hugging Face on 24 July 2026. It has about 8.9 billion parameters.
Its card lists the licence as Apache 2.0. In short, the licence allows commercial use, modification and redistribution, with attribution and a copy of the licence, and includes a patent grant. Access on Hugging Face requires accepting the publisher’s terms first.
Hugging Face counted about 700,250 downloads of it in the 30 days before we checked (7 Oct 2026), and 132 people have liked it there.
02
How much memory it needs
We size it the way you would size any model: the weights (parameters × bits ÷ 8), the KV cache for 8,192 tokens of context, and roughly 1.5 GB for the runtime itself. Real use varies with settings.
The KV cache could not be computed from the published configuration, so add room for context on top of these totals.
Precision
Weights
KV cache (8,192 tokens)
Total, estimated
BF16 (full precision)
18 GB
not computed
19 GB
8-bit (Q8_0)
9.5 GB
not computed
11 GB
4-bit (Q4_K)
5.0 GB
not computed
6.5 GB
03
Will it fit on ANVE?
These verdicts are arithmetic, not tests, against the specification at launch: ANVE One can give a model about three quarters of its 64 GB of unified memory, while ANVE Office and ANVE Office Pro hold it on a 24 GB graphics card and keep the rest of the stack in 64 GB or 128 GB of system memory. ANVE’s tested default is Qwen 3.8 27B; this model is not yet validated on ANVE.
Configuration (at launch)
Memory for the model
Verdict
ANVE One
about 48 GB of 64 GB unified memory
fits at BF16
ANVE Office
24 GB on the RTX PRO 4000 Blackwell SFF Edition
fits at BF16
ANVE Office Pro (GPU)
24 GB on the RTX PRO 4000 Blackwell
fits at BF16
04
What an office would use it for
This size suits quick drafting, classification, extraction and chat over short documents on modest hardware. ANVE pairs a fast 4B-class model with its main model for quick jobs.
05
Similar models to compare
Qwen3-VL-8B-Instruct (8.8B parameters, about 6.4 GB at 4-bit before context; commercial use allowed)
Llama-3.1-Nemotron-Nano-VL-8B-V1 (8.7B parameters, about 6.4 GB at 4-bit before context; custom licence: check before commercial use)
MiniCPM-V-4_5 (8.7B parameters, about 6.4 GB at 4-bit before context; commercial use allowed)
06
Questions people ask
How much memory does Apertus-v1.5-8B need?
About 6.5 GB at 4-bit, 11 GB at 8-bit and 19 GB at full 16-bit precision, including about 1.5 GB of runtime overhead. These are estimates from its parameter count.
Can Apertus-v1.5-8B run on a 24 GB graphics card?
Yes, at BF16 by this estimate, with room left for context.
Is Apertus-v1.5-8B free for commercial use?
Its card lists Apache 2.0, which allows commercial use, modification and redistribution, with attribution and a copy of the licence, and includes a patent grant. Read the licence itself before relying on this summary; it is not legal advice.
07
What is not real yet
No sealed ANVE unit exists; every image of the appliance on this site is a labelled render. The software runs today on a development machine. No customers yet, no certifications, no delivery date, and the final price is not announced.
Reservations are ₹999 in India or US$12 elsewhere, refundable in full until you confirm an order in writing (terms). Offices that cannot use cloud AI can apply to be one of ten design partners.
