Google: Gemma 3n 2B (free)
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.
Description
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.
ArchitectureАрхитектура
- Modality:
- text->text
- InputModalities:
- text
- OutputModalities:
- text
- Tokenizer:
- Other
ContextAndLimits
- ContextLength:
- 8192 Tokens
- MaxResponseTokens:
- 2048 Tokens
- Moderation:
- Disabled
PricingRUB
- Request:
- ₽
- Image:
- ₽
- WebSearch:
- ₽
- InternalReasoning:
- ₽
- Prompt1KTokens:
- ₽
- Completion1KTokens:
- ₽
DefaultParameters
- Temperature:
- 0
UserComments