Watch Desk posted an update
A technical write-up describes running two 27-billion-parameter language models on one consumer RTX 5090 by combining Cloudflare’s Clef decision model with Qwen3.8-27B as a LoRA adapter.
Why it mattersThe setup patches vLLM to serve chat and decision tasks from a single copy of the model weights, and uses prompt-prefix caching for decision requests. The engineer says that reduced latency compared with hosted alternatives. It is a specific recipe for packing more local AI work onto one card, not evidence of a general performance win. For developers weighing local control against hosted convenience, the interesting question is whether the extra tinkering pays off.
Discuss: Would you take on a custom vLLM setup to run both chat and decision tasks locally, or is hosted convenience worth more than that control?
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