Contamination Map Methodology

Text / LLM / Model

Gemma 3n

Organisation
Google DeepMind
Family
Gemma · version 3n
Released
2025-06-26 (Google Developers Blog 'Introducing Gemma 3n: The developer guide' dated June 26, 2025)
Training cutoff
2024-06-01
Evidence
“The knowledge cutoff date for the training data was June 2024.”
ai.google.dev · model card · Model Data / Training Dataset · retrieved 2026-10-15
Checkpoints
google/gemma-3n-E2B, google/gemma-3n-E4B, google/gemma-3n-E2B-it, google/gemma-3n-E4B-it
Weights
Open · Gemma Terms of Use
Links
Model card

Training data disclosure: Vague

Level determined for 9% of benchmark cells.

“These models were trained on a dataset that includes a wide variety of sources totalling approximately 11 trillion tokens.”
ai.google.dev · model card · Model Data / Training Dataset · retrieved 2026-10-15

Other declared training data

Benchmark cells

Classic LLM benchmarks

Unknown MMLU (Measuring Massive Multitask Language Understanding) · training data not disclosed in enough detail

Unknown GSM8K (Grade School Math 8K) · training data not disclosed in enough detail

Unknown MATH (Mathematics Aptitude Test of Heuristics) · training data not disclosed in enough detail

Unknown HumanEval · training data not disclosed in enough detail

Unknown ARC-Challenge (AI2 Reasoning Challenge, Challenge Set) · training data not disclosed in enough detail

Unknown HellaSwag · training data not disclosed in enough detail

Unknown TruthfulQA · training data not disclosed in enough detail

Unknown WinoGrande · training data not disclosed in enough detail

Multimodal LLM benchmarks

Unknown MMMU (Massive Multi-discipline Multimodal Understanding and Reasoning) · training data not disclosed in enough detail

Unknown MMMU-Pro · training data not disclosed in enough detail

Unknown MathVista · training data not disclosed in enough detail

Unknown ChartQA · training data not disclosed in enough detail

Unknown DocVQA · training data not disclosed in enough detail

Unknown AI2D (AI2 Diagrams) · training data not disclosed in enough detail

Not seen CharXiv · its test items were published from 2024-06-26, after the model's stated training-data cutoff (2024-06-01)

Evidence (3)
“The knowledge cutoff date for the training data was June 2024.”
ai.google.dev · model card · Model Data / Training Dataset · retrieved 2026-10-15
“arXiv:2406.18521v1 [cs.CL] 26 Jun 2024”
arxiv.org · paper · arXiv v1 header · retrieved 2026-10-15
“we release all QA pairs for the validation set and keep the answers to the test set private to prevent data leakage.”
arxiv.org · paper · Section 3, footnote 4 · retrieved 2026-10-15

Recent LLM benchmarks

Unknown GPQA Diamond · training data not disclosed in enough detail

Unknown MMLU-Pro · training data not disclosed in enough detail

Unknown LiveCodeBench (code generation, release_v6) · training data not disclosed in enough detail

Unknown SWE-bench Verified · training data not disclosed in enough detail

Unknown AIME 2024 · training data not disclosed in enough detail

Not seen AIME 2025 · its test items were published from 2025-02-06, after the model's stated training-data cutoff (2024-06-01)

Evidence (3)
“The knowledge cutoff date for the training data was June 2024.”
ai.google.dev · model card · Model Data / Training Dataset · retrieved 2026-10-15
“2025 AIME I problems and solutions. The test was held on Thursday, February 6, 2025.”
web.archive.org · website · retrieved 2026-10-15
“This year the AIME I will take place on February 6, 2025, while the alternate AIME II will take place on February 12, 2025.”
maa.org · website · retrieved 2026-10-15

Unknown MATH-500 · training data not disclosed in enough detail

Notes

No technical report; post-training data not described. Accepts image input: “They are capable of multimodal input, handling text, image, video, and audio input, and generating text outputs”

Sources