Google's free Gemma 4 model runs on hardware you probably already own
… Related Google's Gemma 4 isn't the smartest local LLM I've run, but it's the one I reach for most Google's newest Gemma 4 models are both powerful and useful. …
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Google Gemma
Gemma is a family of open-weight language models released by Google for text generation and related NLP tasks.
I thought I needed a GPU for local LLMs until I tried this lean model
… My real-life experience with Gemma 4 models Eye-opening adventure My journey into the Gemma 4 ecosystem didn’t start with the lightweight models — I actually went straight for the heavy hitter: 26B A4B. …
I finally found an open-source local LLM that actually competes with cloud AI
… It's under Apache 2.0, which is a bigger deal than it sounds - previous Gemma releases had Google's own restrictive terms attached, so this was the first time you could actually take the weights, fine-tune them, build something commercial, and not have to read the fine print. …
Google's Gemma 4 finally made me care about running local LLMs
… You can run Gemma 4 models on your phone or laptop for free It's easier than you think As I just mentioned above, Gemma 4 models have been intentionally engineered to get the most out of every parameter. …
I ran a powerful local AI model on my laptop, and it didn’t feel like a compromise
… Gemma 4 12B is the solution Right-sized architecture The arrival of Google DeepMind’s Gemma 12B changes the scenario. …
Google's Gemma 4 isn't the smartest local LLM I've run, but it's the one I reach for most
… Google's new Gemma 4 models don't eliminate that trade-off entirely, but it comes closer than anything else I've tried. What makes Gemma 4 different from previous open-weight releases is the sheer range of what Google shipped. …
I put Google's Gemma 4 on my homelab and Tailscale on my phone — and cancelled Claude Pro
… The next step was to select the best Gemma 4 model for my PC, based on my mobile usage. The Gemma 4:26b was overkill and wouldn't fit in 12GB VRAM. So I decided to move ahead with gemma4:e4b — adequate 128K context window, 9.6GB in size, and both text and image support. …
I turned my phone into a local LLM server, and it handles vision, voice, and tool calls
… It's still more powerful and faster than Gemma E4B, but the fact it works at all here is impressive. It's still bleeding edge; while Gemma 4 E4B has a native audio conformer encoder, the support is very new. …
I ran Gemma 4 (26B) on a 10-year-old-GPU, and it's reliable enough to replace the cloud
… After increasing the RAM size to 24GB and restarting the llama.cpp server, Gemma 4 managed to hit a whopping 15 t/s! …
I tried Google's new DiffusionGemma, and watching it generate text like an image is unlike any local LLM
… DiffusionGemma is not a straight upgrade over Gemma 4 Google says quality is the trade-off The name makes DiffusionGemma sound like another member of the Gemma family, which it is, but the model has a very different goal. …