is_available() reported false in the running engine even though gptqmodel + fast
kernels import fine in a fresh process. Two causes:

1. capabilities() cached a DEGRADED result (gptqmodel imported but the inner
   gptqmodel.utils.backend BACKEND import transiently came up empty, e.g. when the
   first call landed mid model-load). That empty-backends result stuck for the whole
   process life, so the settings page said "GPTQModel not installed" until restart.
   Now a degraded (available-but-no-backends) result is NOT cached — re-detect next
   call; only a clean positive or a genuine ImportError is cached.

2. is_available() gated on a SPECIFIC fast kernel being detected. GPTQModel always
   has a Triton/torch fallback and picks the kernel at load, so availability now
   gates only on gptqmodel importing; backends stay informational.

Also: /admin/api/quantize-capabilities re-detects live (capabilities(refresh=True))
so the settings page never serves a stale cache.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RdMufYvtTbtGDWsiZVoXce