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Run it on your own hardware · updated 2026-10-16

gemma-3-12b-it
The memory it needs, what you may do with it, and the hardware it suits.

Short answer. gemma-3-12b-it needs about 12 GB of memory at 4-bit, 18 GB at 8-bit and 29 GB at full 16-bit precision, including runtime overhead and an 8,192-token KV cache. It has about 12.2 billion parameters and a 131,072-token context window. Licence in short: commercial use allowed, with conditions. By memory alone, on ANVE’s launch configurations: ANVE One fits at BF16, ANVE Office fits at 8-bit, ANVE Office Pro (GPU) fits at 8-bit. These are estimates from its published size, not benchmarks.

01

What it is

gemma-3-12b-it is a vision-language model: it reads images (scanned pages, photos, charts and screenshots) as well as text, published by Google on Hugging Face on 1 March 2025. It has about 12.2 billion parameters and a configured context window of 131,072 tokens.

Its card lists the licence as Gemma Terms of Use. In short, the licence allow commercial use, subject to Google’s prohibited use policy, and require the terms to be passed on with the model. Access on Hugging Face requires accepting the publisher’s terms first.

Hugging Face counted about 444,148 downloads of it in the 30 days before we checked (7 Oct 2026), and 856 people have liked it there.

It is built on google/gemma-3-12b-pt, according to its card.

02

How much memory it needs

How these figures are worked out: weights = parameters × bits per weight ÷ 8. The KV cache is added for 8,192 tokens of context, plus about 1.5 GB of runtime overhead. Treat the totals as planning estimates.

Each token of context adds about 0.39 MB of KV cache at 16-bit, so 32,768 tokens would add about 13 GB. Some layers use sliding-window attention, so the real cache is smaller than this full-attention estimate.

PrecisionWeightsKV cache (8,192 tokens)Total, estimated
BF16 (full precision)24 GB3.2 GB29 GB
8-bit (Q8_0)13 GB3.2 GB18 GB
4-bit (Q4_K)6.9 GB3.2 GB12 GB
03

Architecture at a glance

SettingValue in config.json
Architecture classGemma3ForConditionalGeneration
Model typegemma3
Layers48
Hidden size3,840
Attention heads16
Key-value heads8 (grouped-query attention)
Head size256
Vocabulary262,208
Configured context131,072
Stored precisionbfloat16
04

Will it fit on ANVE?

How the verdicts are worked out: on ANVE One, about three quarters of 64 GB of unified memory is available to the model; on ANVE Office and ANVE Office Pro, the model has to fit in the 24 GB on the graphics card, with 64 GB or 128 GB of system memory for everything else. This is arithmetic against the launch specification, not a test. ANVE’s tested default is Qwen 3.8 27B; this model is not yet validated on ANVE.

Configuration (at launch)Memory for the modelVerdict
ANVE Oneabout 48 GB of 64 GB unified memoryfits at BF16
ANVE Office24 GB on the RTX PRO 4000 Blackwell SFF Editionfits at 8-bit
ANVE Office Pro (GPU)24 GB on the RTX PRO 4000 Blackwellfits at 8-bit
05

What an office would use it for

This is the class ANVE runs by default (27B-class): strong enough for meeting minutes, summaries, drafting and question answering over an office’s own documents, and small enough for one box.

06

Similar models to compare

  • Llama-3.2-11B-Vision-Instruct (10.7B parameters, about 7.5 GB at 4-bit before context; commercial use allowed, with conditions)
  • GLM-4.1V-9B-Thinking (10.3B parameters, about 7.3 GB at 4-bit before context; commercial use allowed)
  • GLM-4.6V-Flash (10.3B parameters, about 7.3 GB at 4-bit before context; commercial use allowed)
07

Questions people ask

How much memory does gemma-3-12b-it need?
About 12 GB at 4-bit, 18 GB at 8-bit and 29 GB at full 16-bit precision, including an 8,192-token KV cache and about 1.5 GB of runtime overhead. These are estimates from its parameter count.
Can gemma-3-12b-it run on a 24 GB graphics card?
Yes, at 8-bit by this estimate, with room left for context.
Is gemma-3-12b-it free for commercial use?
Its card lists Gemma Terms of Use, which allow commercial use, subject to Google’s prohibited use policy, and require the terms to be passed on with the model. Read the licence itself before relying on this summary; it is not legal advice.
What is gemma-3-12b-it’s context window?
Its configuration sets 131,072 tokens. Longer contexts need more memory for the KV cache, so the practical limit on a given machine can be lower.
08

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.