Google: Gemma 3n 2B (free)
Google's Gemma 3n 2B is a very small free model with minimal benchmark scores across all dimensions — suitable only for the lightest experimental tasks and not recommended for professional business use.
Assessment date: March 12, 2026
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Gemma 3n E2B IT is a multimodal, instruction-tuned model developed by Google DeepMind, designed to operate efficiently at an effective parameter size of 2B while leveraging a 6B architecture. Based on the MatFormer architecture, it supports nested submodels and modular composition via the Mix-and-Match framework. Gemma 3n models are optimized for low-resource deployment, offering 32K context length and strong multilingual and reasoning performance across common benchmarks. This variant is trained on a diverse corpus including code, math, web, and multimodal data.
Architecture
| Modality | Text → Text |
| Tokenizer | Other |
| Parameters | 2B |
Performance Indices
Source: Artificial Analysis
Benchmark Scores
Evaluations
Benchmark data from Artificial Analysis and Hugging Face
Model Information
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
