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Gemma 4 E4B

Gemma 4 E4B is an open-weight language model from Google DeepMind, released on April 2, 2026.

Developer
Google DeepMind
Released
April 2, 2026
Total parameters
8B
Architecture
Dense
Context window
128K
Input
Text, image, audio
License
Apache 2.0
Commercial use
Yes
Official weights, GB
16 GB
Hugging Face repository
huggingface.co
Checked on

Gemma 4 E4B is a dense model with 8B parameters. Google describes it as having 4.5B effective parameters. Google DeepMind lists a context window of 128K tokens. The model accepts text, image and audio input. The weights are released under Apache 2.0, which allows commercial use. The official weights on Hugging Face take about 16.0 GB in BF16. Running the model needs at least that much memory across GPUs and system RAM, plus room for the context cache; quantized versions need less.

Total parameters, billions
8B
Context window, tokens
128K
License type
Apache 2.0
License conditions
Apache 2.0: keep the license and notices; no limits on field of use or number of users. Gemma 4 is the first Gemma generation under Apache 2.0; earlier versions used the Gemma Terms of Use.
Weights precision
BF16
Official quantized or alternative versions
google/gemma-4-E4B-it-qat-q4_0-gguf; google/gemma-4-E4B-it-qat-q4_0-unquantized; google/gemma-4-E4B-it-qat-w4a16-ct; google/gemma-4-E4B-it-qat-mobile-ct; google/gemma-4-E4B-it-qat-mobile-transformers
License text
ai.google.dev
Sources
PageURL
Hugging Face model cardhttps://huggingface.co/google/gemma-4-31B-it/raw/main/README.md
blog.google announcementhttps://blog.google/innovation-and-ai/technology/developers-tools/gemma-4/
opensource.googleblog.com announcementhttps://opensource.googleblog.com/2026/03/gemma-4-expanding-the-gemmaverse-with-apache-20.html
Hugging Face APIhttps://huggingface.co/api/models?author=google&search=gemma-4

Questions

Is Gemma 4 E4B free for commercial use?
Yes. Gemma 4 E4B is released under Apache 2.0: keep the license and notices, with no limits on field of use or number of users. Gemma 4 is the first Gemma generation under Apache 2.0.
What does E4B mean?
Google describes Gemma 4 E4B as having 4.5B effective parameters, although it has 8B parameters in total.
Can Gemma 4 E4B run on a 16 GB GPU?
The official BF16 weights alone take about 16.0 GB, before the context cache, so a 4-bit build is the safer choice; check your setup with the memory calculator.
Which smaller Gemma 4 E4B builds are there?
Google publishes quantization-aware versions of Gemma 4 E4B: GGUF (q4_0), W4A16 and two mobile builds, google/gemma-4-E4B-it-qat-mobile-ct and google/gemma-4-E4B-it-qat-mobile-transformers.
How does Gemma 4 E4B compare with Gemma 4 E2B?
Gemma 4 E4B has 8B parameters and a 16.0 GB download; Gemma 4 E2B has 5.1B parameters and a 10.2 GB download.

Sources

Every figure comes from the developer’s model card, license text and official announcements, and from the model’s Hugging Face repository metadata. Each model page lists its sources and the date they were checked; the register is rechecked every week.

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