Running Gemma 4 26B on a 13-Year-Old Xeon: Practical AI Performance Without GPUs

Short summary

A tutorial demonstrating how to run Gemma 4 26B on a 13-year-old Intel Xeon E5 v2 server using 4-bit quantization and CPU-specific optimizations. The approach reduces RAM usage from 120GB to ~45GB and achieves ~12 tokens/sec, making LLM inference feasible on legacy hardware at ~15% of GPU costs. Includes code snippets, performance benchmarks, and tuning tips for Intel MKL optimizations.

• •Gemma 4 26B runs on legacy Xeon CPUs using 4-bit quantization, reducing RAM to ~45GB
• •Achieves ~12 tokens/sec on a 13-year-old Xeon E5 v2 with 64GB RAM
• •Includes code examples, performance metrics, and Intel MKL optimization tips

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