Hybrid orchestrationGenesis archive2026-09
Building a two-server local AI ecosystem across 17 GPUsA self-hosted AI ecosystem spans two Linux servers, assigning different GPUs to long-context coding, inference, speech, RAG and media workloads.
Capacity range
Exact reported VRAM
Practice
Model
Quantization
Context length
Reported speed
Runtime
Tools / workflow (harness)
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
3 resultsEvery record keeps its origin visible.
Batch utilityGenesis archive2026-09
Generating 60,000 helpdesk tickets overnight instead of burning API creditsA 3080 churned for about 18 hours to produce roughly 60,000 synthetic helpdesk tickets, complete with email threads and time entries, for testing a ticketing system.
Hybrid orchestrationGenesis archive2026-09
An overnight local subagent running unfinished work through cronHermes uses a multi-GPU local server as a coding subagent, with cron inventorying unfinished work overnight and a cloud model reviewing the result.