deepmind.google · Open Weight Models
Google DeepMind's lightweight open models built from Gemini research, sized to run on laptops, phones and single GPUs.
Gemma is one of 20 open weight model tools on Axiomi. See all open weight model tools or how we check facts.
// guides
SGLang vs vLLM on DGX Spark compared on setup, memory, NVFP4 models, speed and clustering, so you can pick the right server for your GB10 desktop.
SmolLM vs Gemma compared on size, licence, context, languages, vision and audio, local setup and fine tuning, so you can pick the right small model in 2026.
LLM distillation vs quantization: distillation trains a smaller student model, quantization stores the same weights in fewer bits. When to use each, or both.
Run Gemma 4 locally with Ollama, llama.cpp or LM Studio: pick E2B, E4B, 12B, 26B-A4B or 31B by memory, thinking mode, vision tips and sampling settings.
Wire a local LLM into VS Code with Ollama: official Chat extension, Continue.dev for tab complete, model picks by VRAM, and privacy tips for offline coding.
Open source LLM models to run locally: match Qwen3, Gemma 4, gpt-oss and DeepSeek R1 distill tags to your VRAM, with Ollama setup and licence caveats.
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