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Open-weight model · Any to any

gemma-4-E2B-it-qat-w4a16-ct

by Google google/gemma-4-E2B-it-qat-w4a16-ct

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.

Parameters5.6B
Context131,072
Weights8.3 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads404.9k

Runs On

What it takes to serve gemma-4-E2B-it-qat-w4a16-ct (5.6B 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 11.1 GB 13.4 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 5.6 GB 6.7 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 2.8 GB 3.3 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.

SAVRN's Notes on gemma-4-E2B-it-qat-w4a16-ct

Three precisions, one card, and the decision comes down to concurrency. At 4-bit this model needs 3.3 GB for 2.8 GB of weights; at 8-bit, 6.7 GB for 5.6; at 16-bit, 13.4 GB for 11.1. All three fit the cheapest setup, one MI300X with 192 GB at $1.85 per hour on-demand, so precision decides how many sessions share the card and how much of the 131,072-token context each gets, not whether it fits. Underneath: 5.6B parameters, text and image in, audio on this E2B size, text out.

Apache 2.0 keeps the deployment simple: commercial use, modification and redistribution, provided the license and copyright notices stay and significant changes are stated. Two checks. It is quantized from google/gemma-4-E2B-it-qat-q4_0-unquantized, so read the Gemma 4 technical report, arXiv:2607.02770, for what changed. And the publisher describes a context window of up to 256K tokens while the configuration says 131,072; plan on 131,072.

Model Card

By Google, published under apache-2.0, revision 971342c08f60.

Read the full model card (3,619 words)

Configuration

Architecture
Gemma4ForConditionalGeneration
Context length (tokens)
131,072
Layers
35
Hidden size
1,536
Feed-forward size
6,144
Attention heads
8
Key/value heads
1
Head dimension
256
Vocabulary size
262,144
Sliding window (tokens)
512
Model type
gemma4
Quantization
compressed-tensors

Identity and Version

Repository
google/gemma-4-E2B-it-qat-w4a16-ct
Publisher
Google
Task
Any to any
Modality
Multimodal
Library
transformers
Parameters
5.6B parameters
Languages
Not stated by the source
Revision
971342c08f607aa7779983f6b5289778b5d271a7
First published
2026-06-04
Last updated
2026-07-20

Files and Weights

9 files, 8.3 GB in total. The weights are 1 file totalling 8.3 GB in safetensors.

Weights1 file · 8.3 GB
Configuration3 files · 24.1 KB
Tokenizer2 files · 32.2 MB
Documentation1 file · 29.4 KB
Other1 file · 18.6 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights8.3 GB 93177bfc1b53
config.jsonConfiguration22.2 KB
generation_config.jsonConfiguration208 B
processor_config.jsonConfiguration1.7 KB
README.mdDocumentation29.4 KB
chat_template.jinjaOther18.6 KB
.gitattributesRepository1.6 KB
tokenizer.jsonTokenizer32.2 MB cc8d3a0ce364
tokenizer_config.jsonTokenizer3.7 KB

License and Download

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

Released by Google through Kaggle. Read the license.

Built From

Memory Requirements

PrecisionWeights in memory
As published8.3 GB
16-bit11.1 GB
8-bit5.6 GB
4-bit2.8 GB

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

Questions About gemma-4-E2B-it-qat-w4a16-ct

How much GPU memory does gemma-4-E2B-it-qat-w4a16-ct need?

About 13.4 GB at 16-bit and 3.3 GB at 4-bit: the weights (5.6B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run gemma-4-E2B-it-qat-w4a16-ct 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-E2B-it-qat-w4a16-ct commercially?

Yes. gemma-4-E2B-it-qat-w4a16-ct 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-E2B-it-qat-w4a16-ct's context length?

131,072 tokens, from the maximum position embeddings in its published configuration.

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