Galahad

Headlines · 1

1. Oct 18
   Corbenic's Galahad puts KV cache on server SSDs; its 14x claim draws scrutiny

   TechRadar reports that Belgian startup Corbenic AI's Galahad, in beta since October 1 2026, writes a model's KV cache to encrypted local NVMe storage and reloads it after GPU memory is cleared or the server restarts, so the model need not reread the same text. Founder Sietse Schelpe says it needs only Linux, an Nvidia GPU and a standard NVMe drive, with no special hardware. The report notes, however, that the headline 14x figure owes most to a retrieval component called Blaise, which hands the model roughly 668 tokens instead of the whole corpus; with the KV component Taliesin alone, vLLM took 15.56 seconds per question versus an 8.11-second baseline, and SGLang 22.02 versus 10.29. It also notes that LMCache, Nvidia Dynamo, WEKA and Phison already persist KV cache to storage, and that Corbenic's numbers come from the founder's own runs on rented cloud GPUs in self-published preprints, with raw logs not yet released.

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