With 49–96 GB,
here is what really runs.
Experiences reported by people using their machines every day. The figure is the reported setup capacity; multi-GPU and unified-memory layouts can behave differently.
in this range
Coding a SaaS product on an M1 Max, one well-scoped feature at a time
Running Qwen 3.8 27B on the same Mac they work on, this developer credits per-feature domain glossaries and tight scoping — not the model — for making local coding reliable.
Using a local model to stress-test the agent a coding agent is building
An unusual layered setup: the local model isn't the coding agent — it's the thing an outer coding agent uses to build and stress-test a separate 'inner' agent.
Coding and homelab maintenance on a dual-R9700 server
A garage server with two Radeon Pro AI R9700 cards supports coding, homelab maintenance and an evolving Cline/Open WebUI workflow.
A local-first portfolio tracker fed private financial documents all day
Three GPUs spread across machines run Qwen 3.8 27B through a custom stateful agent layer to build a personal finance and portfolio tracker without shipping documents to the cloud.
A cloud-free workstation: RTX Pro 6000, vLLM and a DeepSeek harness
A custom Linux workstation with an RTX Pro 6000 and 48GB of RAM runs programming, copy editing and summarisation through vLLM, with no cloud use all year.
A workstation GPU as a drop-in subagent for Codex and Claude
Qwen 3.8 Flash Next on an RTX Pro 6000 takes implementation and review tasks delegated from Codex or Claude, replacing Sonnet and Opus for that slice.
Two RTX 5090s running helpdesk and ops for a small office
An office replaced roughly $2,000 a month of API consumption with two RTX 5090 machines running Qwen 3.8 27B under vLLM, one for helpdesk and one for ops.
A Tesla V100 32GB and an RTX 3090 on Strata: Qwen 3.8 Flash Next at 262K context for local business management
Two single-GPU Ubuntu servers, one with a blower-modded Tesla V100 32GB and one with an RTX 3090, run Strata with Qwen 3.8 Flash Next at 262K context for local business management automation.
Three rigs for freelance work an NDA won't let leave the building
Client confidentiality rules out cloud APIs for this freelancer, who spreads different model sizes across three separate machines.
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Every capacity guide, or start from your own machine and a task.