Google Seeks Gemma Roadmap Input; Community Demands 100B-1T Parameter Models

Google's Gemma team recently launched a community survey to gather capability requests and expectations for its next-generation models to clarify its future roadmap. The team noted that Gemma's adoption rate has grown steadily over the past three years, highlighting its core advantages of being smaller, easy to self-deploy, and highly suitable for local or hybrid smart applications on phones and laptops. It is also praised as a high-quality open-weights model ideal for industrial fine-tuning.

Confirmed

The specific developer requests gathered by the team are very clear. AI researcher @natolambert urged Google to release a 100-billion (100B) parameter-level Gemma model to demonstrate a genuine commitment to the open-source ecosystem. Furthermore, @xjdr strongly demanded the development of a true base model with 1T+ (trillion-level) parameters, pointing out that the open-weights sector is highly competitive and Gemma needs larger models to increase its impact. Other key feedback from the community includes requests for broader knowledge coverage, better front-end aesthetics, and enhanced visual-language judgment and reward capabilities.

Why it matters

This survey not only reflects Google's intent to improve the practicality and openness of its open-source models but also highlights a core contradiction within the current open-source ecosystem. Although lightweight models perform exceptionally well in edge-side and local deployments, developers still have a strong craving for ultra-large parameter base models to meet increasingly complex general-purpose application needs. Whether Gemma can strike a balance between its edge-side advantages and base model scale will determine the market competitiveness of its next-generation products.

2026-07-25 ~ 2026-07-27 · 9 related posts

• Google’s Gemma open-weight models are being praised for strong industrial fine-tuning — clmt · 2026-07-25
• [source] KOL Calls on Google to Release 100B Parameter Gemma 4 Model — natolambert · 2026-07-26
• Researcher to Google: Time to Release a 100B Parameter Gemma Model — QuixiAI · 2026-07-26
• Google says Gemma adoption has grown steadily for 3 years as local AI use expands — OlivierBachem · 2026-07-26
• [source] Google’s Gemma team asks what capabilities people want in the next models — osanseviero · 2026-07-26
• Google’s Gemma team asks what capabilities to add in the next models — andrew_n_carr · 2026-07-27
• [source] Developers to Google: Give Us a 1T+ Parameter Base Model for Next Gemma — _xjdr · 2026-07-27
• Gemma needs a larger base model to matter more in open weights — _xjdr · 2026-07-27

1 near-duplicate retellings: deliprao