# Reranking Capability

`rag.reranking@1` is a first-class capability, never a public model or worker endpoint. A caller
submits one query, 1–40 bounded `{id,text}` documents and `top_n` 1–10. The response contains only
stable IDs, finite scores and ranks. ModelForge resolves the experiment deployment, acquires a GPU
lease and dispatches to the private GPU Node runtime worker.

Query and document text exist only in the bounded Redis payload exchange and worker memory. They
are deleted after completion or timeout and never enter PostgreSQL, audit payloads, metrics or
request history. IDs, timings, counts and failure codes may be persisted. There is no network
egress, cloud fallback or `trust_remote_code` path.

The M8 implementation supports the Qwen3 causal-LM reranker adapter with immutable runtime-profile,
artifact-set, exact-revision and probe evidence. Typed failures include `RERANKER_NOT_AVAILABLE`,
`RERANK_REQUEST_TOO_LARGE`, queue/capacity failures and invalid/non-finite output.

The M8 deployment is experiment-only. No stable route or production promotion was created.