Enterprises facing data-residency constraints must self-host LLMs, but adopting newer models without retiring older ones fragments GPU resources. A technical report describes consolidating traffic from over 200 internal applications onto a single self-hosted model by closing quality gaps through post-training, covering the corporate request mix.
Data-residency constraints force enterprises to self-host LLMs, but continuous adoption of newer models without decommissioning their predecessors expands the serving fleet, fragmenting a finite GPU pool. We consolidate traffic from over 200 internal applications onto a single model by closing quali
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