A 4 GB Laptop GPU Beats a 12-Core CPU by 4.3x on Gemma 4

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https://dev.to/gde/a-4-gb-laptop-gpu-beats-a-12-core-cpu-by-43x-on-gemma-4-4150

A 4 GB Laptop GPU Beats a 12-Core CPU by 4.3x on Gemma 4 - DEV Community

Serving Gemma 4 E2B q4_0 through llama.cpp on one laptop, twice: CPU-only and on a 2021-era 4 GB GTX 1650 Ti. Same GGUF, same binary, same prompts, one flag apart. The card takes decode by 4.3x, and needs only 1598 MiB to do it.

Gemma 4 on an Old 4 GB Laptop GPU: QAT Takes It From 9.5 GiB to 1.6 - DEV Community

https://dev.to/gde/gemma-4-on-an-old-4-gb-laptop-gpu-qat-takes-it-from-95-gib-to-16-b5l

Three Gemma 4 Deployments on One T4G for Under $3: What the Runtime Changes, and What It Doesn't - DEV Community

https://dev.to/aws-builders/three-gemma-4-deployments-on-one-t4g-for-under-3-what-the-runtime-changes-and-what-it-doesnt-2cin

Gemma 4 QAT on 10GB Laptop: Local AI with 6.7GB VRAM - DEV Community

https://dev.to/everylocalai/gemma-4-qat-on-10gb-laptop-local-ai-with-67gb-vram-1ihj

Running Gemma 4 on EC2 G5g: Graviton2 AMD with NVIDIA GPU - DEV Community

https://dev.to/aws-builders/running-gemma-4-on-ec2-g5g-graviton2-amd-with-nvidia-gpu-13j

Pure JAX on G5g: Serving Gemma 4 on Graviton and a T4G - DEV Community

https://dev.to/aws-builders/pure-jax-on-g5g-serving-gemma-4-on-graviton-and-a-t4g-3glo

Does Quantization Break Tool-Calling? I Measured It on a 4GB Laptop GPU (BFCL, 3 Seeds, Bootstrap 95% CI) - DEV Community

https://dev.to/happynood/does-quantization-break-tool-calling-i-measured-it-on-a-4gb-laptop-gpu-bfcl-3-seeds-bootstrap-185l

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