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Gemma 4 E2B

Multimodal
Google

Gemma 4 E2B is Google DeepMind's smallest multimodal model with 2.3 billion effective parameters (5.1B with embeddings) and a 128K context window. Supports image, text, and audio inputs. Designed for on-device and edge deployment with Per-Layer Embeddings for efficient inference.

Key Specifications

Parameters
5.1B
Context
-
Release Date
April 2, 2026
Average Score
40.3%

Timeline

Key dates in the model's history
Announcement
April 2, 2026
Last Update
September 10, 2026
Today
September 20, 2026

Technical Specifications

Parameters
5.1B
Training Tokens
-
Knowledge Cutoff
January 1, 2025
Family
-
Capabilities
MultimodalZeroEval

Benchmark Results

Model performance metrics across various tests and benchmarks

Reasoning

Logical reasoning and analysis
GPQA
Self-reported
43.4%

Other Tests

Specialized benchmarks
AIME 2026
No toolsSelf-reported
37.5%
BIG-Bench Extra Hard
Self-reported
21.9%
LiveCodeBench v6
Self-reported
44.0%
MathVision
Self-reported
52.4%
MedXpertQA
MMSelf-reported
23.5%
MMLU-Pro
Self-reported
60.0%
MMMLU
Self-reported
67.4%
MMMU-Pro
Self-reported
44.2%
MRCR v2 (8-needle)
128kSelf-reported
19.1%
t2-bench
RetailSelf-reported
29.4%

License & Metadata

License
apache_2_0
Announcement Date
April 2, 2026
Last Updated
September 10, 2026

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