gemma
Google's Gemma 4 is a small open multimodal family that skips the image encoder News
Google released Gemma 4, an open-weight model family from 2.3 to 31 billion parameters that natively handles vision and audio, including a 12-billion-parameter variant that ingests raw image and audio patches with no separate encoder.
Google Gemma (open weights) Tool
Google's open-weight model family, light enough that developers are now embedding it directly into interactive apps - including a demo running Gemma inside the Godot game engine via Vulkan compute shaders, no Python server required.
Gemma Gem Tool
A Chrome extension that runs Gemma 4 E2B locally through WebGPU using an ONNX build with 4-bit weights, and gives the resulting agent page-reading, clicking, typing, screenshot and JavaScript tools. Worth knowing before you install: the widely quoted ~500MB is the cached download on disk, and the project's own estimates for GPU and system memory during inference are substantially higher and not benchmarked on real devices.
Gemma 4 Tool
Google's downloadable model family (2.3B-31B, dense and MoE) that natively handles text, vision, and audio, including a 12B encoder-free variant and a thinking mode.
Cactus Hybrid (Gemma-4 E2B) Tool
A phone-sized Gemma-4 checkpoint with an attached error probe that scores how likely each answer is wrong and routes low-confidence queries to a cloud model; weights and runtime are public (set CACTUS_CLOUD_STRICT_SSL before using the cloud path).