Gemma 4 now has a 12B middle tier.

Google positions Gemma 4 12B between edge-friendly E4B and the larger 26B MoE model. The 12B release targets local multimodal and agentic work with native audio and a reduced memory footprint.

Family map

Edge-friendly

E4B

Google names E4B as the edge side of the family comparison. Verify its own model card before transferring 12B architecture or hardware claims.

Mid-sized multimodal

12B

The June 2026 release adds native audio, unified encoder-free multimodal processing, and a stated 16GB local-hardware target.

Larger family tier

26B MoE

Google positions 12B between E4B and this larger Mixture-of-Experts model. Compare benchmark and runtime requirements from the exact model cards.

Why 12B matters

A local multimodal target between edge and MoE

Google's source establishes the family placement and specific 12B design. Use the dedicated 12B route before choosing a runtime, checkpoint, quantization, context size, or agent workload.

What remains variable

Runtime fit is measured, not inherited

Memory targets do not include every operating-system, context, cache, audio, image, and tool workload. Test the exact deployment instead of assuming any 16GB machine will have the same result.

Primary source

Introducing Gemma 4 12B Google's June 3, 2026 family placement and model release record.

Gemma 4 12B Inspect the verified architecture, native audio, license, and local-memory boundary. Local agent guide Plan a measured setup without turning a hardware target into a guarantee. Gemini 3.1 Compare a hosted Google model route with different product and access boundaries. DeepSeek V4 Compare another source-aware coding and reasoning route.

Gemma 4 questions, answered

Gemma 4 is Google's open-model family. The June 3, 2026 launch reviewed here places the new 12B model between an edge-friendly E4B tier and a larger 26B Mixture-of-Experts tier.

The detailed source is Google's Gemma 4 12B launch. Architecture, native-audio, memory, license, and ecosystem claims on this page apply to 12B unless explicitly described as family context.

Yes. Google describes Gemma 4 12B as an encoder-free multimodal model that accepts vision and native audio inputs directly through the language-model backbone.

Google targets Gemma 4 12B at laptops with 16GB of VRAM or unified memory. Actual fit depends on checkpoint format, quantization, context, runtime, inputs, and system overhead, so test the exact configuration.

Google says Gemma 4 12B was released under Apache 2.0. Review the distributed checkpoint, notices, acceptable-use requirements, and dependencies for the exact artifact you deploy.

This page does not claim a Flowith model mapping. Google's weights and ecosystem support do not establish availability in the live Flowith workspace.