Google model product
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.
Updated Aug 10, 2026. Default version: Gemma 3n E2B Instructed
Structured fields from the published default version.
This profile uses the latest version under this unique model that has a calculated LLMBoard score. Arena and price are excluded.
Published benchmark records for the scored version Gemma 3n E2B Instructed.
| OpenAI MMLU | 0.2 | 2 | 2 | 0.0% | C | |
| Codegolf v2.2 | 0.1 | 3 | 4 | 33.3% | C | |
| Global-MMLU | 0.6 | 4 | 5 | 25.0% | C | |
| ECLeKTic | 0.0 | 5 | 8 | 42.9% | C | |
| LiveCodeBench v5 | 0.2 | 8 | 9 | 12.5% | C | |
| Global-MMLU-Lite | 0.6 | 11 | 14 | 23.1% | C | |
| HiddenMath | 0.3 | 11 | 13 | 16.7% | C | |
| WMT24++ | 0.4 | 20 | 23 | 13.6% | C | |
| MGSM | 0.5 | 29 | 31 | 6.7% | C | |
| Include | 0.4 | 30 | 31 | 3.3% | C | |
| MMLU-ProX | 0.1 | 31 | 32 | 3.2% | C | |
| MBPP | 0.6 | 33 | 37 | 11.1% | C | |
| HumanEval | 0.7 | 67 | 76 | 12.0% | C | |
| LiveCodeBench | 0.1 | 68 | 73 | 6.9% | C | |
| MMLU | 0.6 | 98 | 100 | 2.0% | C | |
| AIME 2025 | 0.1 | 113 | 114 | 0.9% | C | |
| MMLU-Pro | 0.4 | 125 | 129 | 3.1% | C | |
| GPQA | 0.2 | 228 | 233 | 2.2% | C |
Preference and agent-evaluation signals from published Arena datasets.
The default version has no published Arena rows, or its source alias has not been resolved.
Official vendor API PAYG pricing is summarized first. The table then lists individual provider offerings without treating their minimum as the official price.
The default version has no provider offering with current input or output token prices.
Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.
All published versions linked to this unique model. The score columns identify the version used by the current overall ranking.
| Gemma 3n E2B | N/A | 8B | N/A | N/A | No | Proprietary | |
| Gemma 3n E2B Instructed | 6.9 | 8B | N/A | N/A | No | Proprietary |
A concise description based on the published model registry.
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.
Use the benchmark, Arena and pricing sections above as separate evidence. A missing field means the current data snapshot does not support that claim.
Data snapshot: 2026-08-07. Editorial model content is not available in the backend.
Open a comparison with the three ranked models immediately above and below this model.
Recommendations prioritize the same model type and family, then the closest published LLMBoard score.
Common questions about Gemma 3n E2B.
Gemma 3n E2B's default version was released on Jun 26, 2025.
No official standard PAYG price is currently available for Gemma 3n E2B.
Gemma 3n E2B is published under Google in the model registry.
The current registry does not publish a context window for the default version.
No. The default version is not marked as having publicly available weights.
No published provider offering is currently linked to the default version.
Nearby ranked alternatives include Gemma 3n E2B LiteRT, ERNIE 4.5, Qwen3 VL 4B.