# Gemma 2B Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/gemma-2b
> Markdown URL: https://aitinkerers.org/technologies/gemma-2b.md
> Technology record last updated: 2026-09-18T14:19:44Z
> Generated: 2026-09-21T14:42:35Z

Gemma 2B: Google's lightweight, open-weight language model (2 billion parameters) delivers best-in-class performance for efficient on-device and cloud deployment.

Gemma 2B is Google's highly efficient, open-weight language model, built directly from the research and technology behind the Gemini models. With 2 billion parameters, this decoder-only LLM is engineered for maximum performance at a minimal size, making it ideal for resource-constrained environments like laptops and edge devices. It supports an 8192-token context length and excels across core text-generation tasks: question answering, summarization, and reasoning. The model’s small footprint and open licensing democratize access to state-of-the-art AI, enabling rapid fine-tuning and flexible deployment across various hardware platforms.

- Official technology site: https://huggingface.co/google/gemma-2b
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Dialoguing with Hugging Face's LLMs](https://paris.aitinkerers.org/talks/rsvp_NqwWdDTv8vU)

We are currently developing an experimental project: speech-to-speech. This library, still under development, offers a modular approach to speech-to-speech language models through a pipeline that includes speech-to-text, large language model prompting, and text-to-speech. The pipeline is fully open and modular, with a focus on leveraging models available via the Transformers library on the Hugging Face hub. While current approaches tend to focus on end-to-end models, often citing latency benefits, we have achieved a latency of around 500ms with a few technical tweaks. Moreover, the modular approach allows users to easily switch components: for example, swapping the Gemma 2B model for LLaMA 3.1 8B can be done directly from the CLI.

- Event context: AI Tinkerers - Paris Meetup on October 15th — 2024-10-15 — Paris
- Public talk page: https://paris.aitinkerers.org/talks/rsvp_NqwWdDTv8vU

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