Gemma 3n E4B Instruct

Creator

Google DeepMind

Released

2025-06-26

Intelligence

1.2

Artificial Analysis Index

Coding

3.2

Artificial Analysis Index

In $/1M

$0.06

input tokens

Out $/1M

$0.12

output tokens

Blended $/1M

$0.07

3:1 blended

Speed

0

tokens / sec

Profile

License, openness, and modality — the governance layer.

License

Proprietary

non-commercial

Weights

Closed

API only

Modalities

Parameters

8B

total

Gemma 3n is a multimodal model designed to run locally on hardware, supporting image, text, audio, and video inputs. It features a language decoder, audio encoder, and vision encoder, and is available in two sizes: E2B and E4B. The model is optimized for memory efficiency, allowing it to run on devices with limited GPU RAM. Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. Gemma models are well-suited for a variety of content understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as laptops, desktops or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone. Gemma 3n models are designed for efficient execution on low-resource devices. They are capable of multimodal input, handling text, image, video, and audio input, and generating text outputs, with open weights for instruction-tuned variants. These models were trained with data in over 140 spoken languages.

Capability profile

Category strength across 20 domains, via LLM Stats.

physics
80language
70math
60general
60
reasoning
60creativity
50psychology
50search
20
Via LLM Stats

Benchmark breakdown

Independent evaluation scores, normalized to 0–100.

GPQA Diamond
30
Humanity’s Last Exam
4
MMLU-Pro
49
SciCode
8
LiveCodeBench
15
MATH-500
77
AIME 2025
14
τ²-Bench (agentic)
5
Terminal-Bench Hard
2
IFBench
28
Via Artificial Analysis
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