Every published setup that reports this model, with its machines, quantization, runtime and reported results. Use the directory filters below to narrow by quantization, capacity or runtime.
Observed across 5 published setups. Counts describe what contributors run, not what the model is “good for”.
Capacity is the reported total for this setup. Multi-GPU and unified-memory layouts can behave differently.
A raw CSV export from a sensor goes into a local model that produces a report, a pattern the owner treats as a deterministic automation overseen by the model.
A daily local coder on an RTX 5060 8GB and 32GB of RAM finds responsiveness under memory pressure matters more than benchmark speed.
Hermes uses a multi-GPU local server as a coding subagent, with cron inventorying unfinished work overnight and a cloud model reviewing the result.
A short but clean division of labor: a frontier model decomposes work into tickets, and a local Qwen model implements them on production code, daily.
After trying Claude Code with task-farming and a Qwen-as-orchestrator experiment, this person settled into two parallel workflows — Orca as the local workhorse, and OpenCode or Bionic for solo agent development.
