Two fixes for the performance split OOM loop at large context:

1) The performance "fits on the fast card?" check used expected_vram_gb (WEIGHTS
   only), ignoring the KV cache + compute buffers. A ~20 GB model at 178k ctx looked
   like it fit a 24 GB card → tensor_split=[1.0,0.0] → llama_context creation OOM'd
   (KV didn't fit) in a retry loop. Add a context-scaled KV/compute estimate
   (~n_ctx/16000 + 1.5 GB, calibrated to observed ~10 GB at 178k) to the footprint
   before deciding what fits — tight enough not to over-load the slow card.

2) On llama_context creation failure, progressively offload to CPU: move ~20% more
   layers to CPU and retry, up to 5 times, then fail. A slow CPU-spilled load beats
   a hard failure / crash loop.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>