Gemma AI, Google’s open-source language model, has officially surpassed 150 million downloads—marking a major milestone in the company’s bid to compete in the booming open AI model market. The announcement came from Google DeepMind’s Omar Sanseviero, who shared the update on X over the weekend, adding that developers have also built more than 70,000 variants of Gemma AI on Hugging Face.
This surge in adoption shows how rapidly Gemma AI is growing in popularity since its initial release. And while it still lags behind Meta’s Llama in total downloads, the momentum behind Google’s model family is becoming impossible to ignore.
Google’s Gemma AI Expands with Multimodal Power
Launched in February 2024, Gemma AI was designed as a transparent, lightweight, and open alternative to other foundation models. The suite includes models fine-tuned for both general-purpose and domain-specific tasks, ranging from coding assistance to biomedical research.
Recent updates have introduced multimodal support, allowing Gemma AI to process both text and images. These upgrades bring it closer to competitors like GPT-4 and LLaMA 3, especially in fields that demand reasoning across multiple data types.
Gemma AI also now supports over 100 languages, helping it scale in diverse regions from Latin America to Southeast Asia. This multilingual capability is a key reason behind its rising adoption, especially in research and global enterprise settings.
70K Variants and a Growing Developer Community
The open nature of Gemma AI has sparked significant enthusiasm within the AI community. According to Hugging Face data, developers have created more than 70,000 forks and variants, customizing the base models for everything from legal document summarization to climate modeling.
This level of experimentation shows that Gemma isn’t just another Google product—it’s becoming an ecosystem. By offering compact, tunable models with strong performance benchmarks, Gemma AI gives developers and startups more control over how they implement large language models without relying fully on black-box APIs.
Still Chasing Meta’s Llama in the Download Race
Despite its rapid growth, Gemma AI still trails behind its closest rival: Meta’s Llama model family. As of late April, Llama models had surpassed 1.2 billion downloads, dwarfing Gemma’s figures by nearly 10x.
Why the gap? Timing and licensing play a big role. Meta released Llama much earlier and built stronger name recognition in open-source AI circles. But licensing issues affect both platforms. While marketed as “open,” neither Gemma nor Llama uses a fully permissive license like Apache 2.0. Developers looking to deploy these models in commercial products often face legal ambiguity.
This makes adoption trickier, especially for startups aiming to scale quickly without legal roadblocks. Still, Google’s active updates and ecosystem-building approach might help Gemma AI close that gap faster than expected.
What’s Next for Gemma AI?
Sanseviero’s post didn’t just celebrate the milestone—he also asked the community what they’d like to see in future releases of Gemma AI. Popular responses include better fine-tuning support, smaller quantized versions for edge devices, improved multilingual reasoning, and native integration with Google Cloud tooling.
Given the speed at which Gemma AI has scaled—from zero to 150 million downloads in just over a year—it’s clear that Google plans to keep investing in the platform. The next phase may involve agent-based architectures, smarter retrieval tools, and deeper alignment training for safer and more interpretable outputs.
Whether Gemma can eventually catch up to Llama remains to be seen. But one thing’s certain: Google’s presence in the open-source AI space is growing stronger by the month.
