A contributor experiments with agents, tools and MCP on an 8GB laptop, using lightweight Gemma models to turn constrained hardware into a practical coding playground.
GPU model
Capacity range
Total VRAM
Practice
Model
Quantization
Context length
Reported speed
Runtime
Tools / workflow
Record origin
EXPLORE BY CAPACITY
Start with your machine.
Capacity is the reported total for this setup. Multi-GPU and unified-memory layouts can behave differently.
8 GB or lessLaptops, iGPUs and modest cards9–12 GBEntry-level local inference13–16 GBCurrent mid-range cards17–20 GBRX 7900 XT and compact pro cards21–24 GB3090, 4090 and 7900 XTX class25–32 GB5090 and workstation cards33–48 GBWorkstation and multi-GPU setups49–96 GBLarge multi-GPU and datacenter setups97 GB+Unified memory, servers and clusters
2 resultsEvery record keeps its origin visible.
Homelab opsGenesis archive2026-09
Making an 8GB laptop useful through DIY agent workflowsBusiness automationGenesis archive2026-09
Company email automation kept off the cloud for legal reasonsThis company believes uploading user data to a cloud model would be illegal for their use case, so email and user-text automation runs on a Gemma 4 build on a single Radeon Pro AI R9700.