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Open-weight model · Any to any

gemma-4-12B

by Google google/gemma-4-12B

Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output.

Parameters12B
Context262,144
Weights23.9 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads156k

Runs On

What it takes to serve gemma-4-12B (12B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 23.9 GB 28.7 GB 1x MI300X (192 GB)
Vultr		 $1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 12.0 GB 14.4 GB 1x MI300X (192 GB)
Vultr		 $1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 6.0 GB 7.2 GB 1x MI300X (192 GB)
Vultr		 $1.85 1x H100 $1.99 · 1x MI325X $2.00

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Sep 18, 2026.

Model Card

By Google, published under apache-2.0, revision 023679ed352d.

Hugging Face | GitHub | Launch Blog | Documentation | Technical Report
License: Apache 2.0 | Authors: Google DeepMind

[!Note] This model card is for the Gemma 4 12B Unified model, which is part of the Gemma 4 family of open models. Built with the same multimodal functionality as Gemma 4 E2B and E4B (text, audio, image, and video inputs), it brings native audio and vision understanding directly to local environments without the need for separate encoders. This unified approach to multimodality makes the model encoder-free, offering a deployment size that is perfect for consumer devices and streamlined local execution.

Read the full model card (3,502 words)

Configuration

Architecture
Gemma4UnifiedForConditionalGeneration
Context length (tokens)
262,144
Layers
48
Hidden size
3,840
Feed-forward size
15,360
Attention heads
16
Key/value heads
8
Head dimension
256
Vocabulary size
262,144
Sliding window (tokens)
1,024
Model type
gemma4_unified

Identity and Version

Repository
google/gemma-4-12B
Publisher
Google
Task
Any to any
Modality
Multimodal
Library
transformers
Parameters
12B parameters
Languages
Not stated by the source
Revision
023679ed352de9bb66cc873c9009ce3482585c08
First published
2026-05-23
Last updated
2026-07-15

Files and Weights

8 files, 24.0 GB in total. The weights are 1 file totalling 23.9 GB in safetensors.

Weights1 file · 23.9 GB
Configuration3 files · 6.0 KB
Tokenizer2 files · 32.2 MB
Documentation1 file · 28.3 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights23.9 GB fe054ae05ff7
config.jsonConfiguration4.4 KB —
generation_config.jsonConfiguration233 B —
processor_config.jsonConfiguration1.4 KB —
README.mdDocumentation28.3 KB —
.gitattributesRepository1.6 KB —
tokenizer.jsonTokenizer32.2 MB 12bac982b793
tokenizer_config.jsonTokenizer888 B —

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
23.9 GB
Download from Google

Released by Google through Kaggle. Read the license.

Built From

Evaluations

Each result is shown as reported, with the conditions its reporter stated. None is a SAVRN measurement. A comparison lines two results up only when their configuration, unit and setup are all stated and identical.

BenchmarkConditionsResultReported byRevisionDate
ARTPARK-IISc/Vaani-Benchmark-V1.0 Task Hindi_WERMetric Hindi_WERComparison conditions not established 24.6 Not named
Reported by a third party		 Evaluated revision not stated 2026-06-26

Memory Requirements

PrecisionWeights in memory
As published23.9 GB
16-bit23.9 GB
8-bit12.0 GB
4-bit6.0 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Built on This Model

Questions About gemma-4-12B

How much GPU memory does gemma-4-12B need?

About 28.7 GB at 16-bit and 7.2 GB at 4-bit: the weights (12B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run gemma-4-12B on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use gemma-4-12B commercially?

Yes. gemma-4-12B is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

What is gemma-4-12B's context length?

262,144 tokens, from the maximum position embeddings in its published configuration.

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