High-VRAM GPUs aren't the future of local AI — unified memory and Mixture of Experts models are
["google-gemma","rtx-5090"]
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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.
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Top stories
I tested Gemma 4, Qwen 3.5, and Ministral 3 for vision tasks, and only one understood the assignment
3d agoHugging Face and Cerebras bring Gemma 4 to real-time voice AI
1w ago
aws.amazon.com Amazon SageMaker AI now supports serverless model customization for Gemma 4 models - AWS
1w agoGemma 4's smallest model runs on 3GB of VRAM, and it's the one I actually reach for
1w agoOllama is still the easiest way to start local LLMs, but it's the worst way to keep running them
["ollama","google-gemma","llms","docker"]
The biggest local LLM on your machine is useless if it can't call a single tool, no matter how many parameters it has
…Google's Gemma 4 E2B, a 2.3 billion effective-parameter model with native function calling. It can even run on a phone . Google's own press release calls it "purpose-built…
Discussions and forums
Google's new Gemma 4 12B model is designed to run on any laptop with 16GB of RAM
Google's new Gemma 4 12B model is designed to run on any laptop with 16GB of RAM
12
Gemma 4 for Telephony: From Two AI Models to One – Until I Switched to Chinese
Gemma 4 for Telephony: From Two AI Models to One – Until I Switched to Chinese
4
Show HN: Running Gemma-4 26B at 124 tokens/SEC on a CPU, no GPU
I wanted to know how fast a 26B mixture-of-experts model could run on a desktop CPU with no GPU. Got ~40 tok/s single-stream (lossless) and ~124 batched. The surprising part was the byte budget: for this model you compre…
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