Gemma 4 E2B
MultimodalGemma 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
Other Tests
Specialized benchmarks
AIME 2026
No tools • Self-reported
BIG-Bench Extra Hard
• Self-reported
LiveCodeBench v6
• Self-reported
MathVision
• Self-reported
MedXpertQA
MM • Self-reported
MMLU-Pro
• Self-reported
MMMLU
• Self-reported
MMMU-Pro
• Self-reported
MRCR v2 (8-needle)
128k • Self-reported
t2-bench
Retail • Self-reported
License & Metadata
License
apache_2_0
Announcement Date
April 2, 2026
Last Updated
September 10, 2026
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