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Text model · Gemma

Gemma 3n E4B: RAM and VRAM requirements

Gemma 3n E4B needs about 5.7 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~4.23 GB to download; KV cache and overhead add the rest), or about 8.4 GB at Q8_0. The lightest hardware that runs it is Nvidia GeForce RTX 3060 (12GB).

Gemma family · 8B params · released Jun 2025.

Shopping for hardware? See what runs Gemma 3n E4B →

License gemma · Conditional ↓ 36.9K/mo ♥ 919 on HuggingFace
Q4_K_M GGUF
4.23 GB
Q8_0 GGUF
6.85 GB
Memory @ Q4 (4k)
~5.7 GB
Context
32 k

Q4_K_M and Q8_0 are GGUF download (file) sizes. Memory @ Q4 includes the KV cache and overhead, so it runs larger than the file on disk.

Will it run on your device?

Gemma 3n E4B runs on 33 of 40 tracked devices at Q4_K_M.

33 run well 0 tight fit 7 too small
Fit check Q4_K_M
Yes, it runs fast
needs 5.7 GB usable 10.5 GB
See the full breakdown
$ollama run gemma3n:e4b

Memory breakdown

Weights (Q4_K_M)4.23 GB
+
KV cache (4k)0.7 GB
+
Overhead0.8 GB
=
Total5.7 GB

How context length changes it

4k context ~5.7 GB 32k context ~10.4 GB 128k context ~26.7 GB

Longer context grows the KV cache quickly: Gemma 3n E4B needs ~5.7 GB at 4k but ~26.7 GB at 128k, which can push it past a device that fits it at a short context.

Speed drops too: every token re-reads the KV cache, so at 128k context Gemma 3n E4B generates at roughly ~16% of its short-context speed. How this is estimated.

Quantization sizes

GGUF quantson disk
Quantization Size on disk
Q2_K 3.4 GB est
Q3_K_M 3.9 GB est
Q4_K_M (default) 4.23 GB
Q5_K_M 5.7 GB est
Q6_K 6.6 GB est
Q8_0 6.85 GB
FP16 13.7 GB

Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.

Run it

Ollama
$ ollama run gemma3n:e4b
llama.cpp
$ llama-cli -hf unsloth/gemma-3n-E4B-it-GGUF:Q4_K_M
LM Studio
$ lms get unsloth/gemma-3n-E4B-it-GGUF

Which devices can run Gemma 3n E4B?

Apple Silicon Macs

RAM-only laptops

iPhone & iPad

Android

NVIDIA GPUs

AMD GPUs

Same job, different size

Pick by what fits your memory: step down to free up VRAM, or step up if you have headroom.

Next size down Qwen2.5 Coder 7B 7B Next size up DeepSeek-R1-0528-Qwen3-8B 8.19B

Similar models

Head-to-head

FAQ

How much VRAM or RAM does Gemma 3n E4B need?

At Q4_K_M, Gemma 3n E4B needs about 5.7 GB (weights ~4.23 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~8.4 GB.

What is the Q4_K_M GGUF file size of Gemma 3n E4B?

The Q4_K_M GGUF file is about 4.23 GB to download, and the Q8_0 GGUF is about 6.85 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~5.7 GB of memory at Q4_K_M.

Can Gemma 3n E4B run on a laptop?

Yes, Gemma 3n E4B fits on a 16 GB machine at Q4_K_M and runs on Apple Silicon or a 12 GB+ GPU comfortably.

Can I use Gemma 3n E4B commercially?

Conditionally. Gemma Terms of Use apply to commercial use.

Understand the numbers

Short guides to the ideas behind Gemma 3n E4B's memory and quant figures.

Google's on-device Gemma 3n (MatFormer): about 8B raw params but a ~4B effective memory footprint. Multimodal, built for phones and laptops.

Sources

Last validated 2026-08-03. Memory figures are estimates. See methodology.