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KV cache exceeds serving budget at reference context

Check R35. Runs in the editor as you build, in CI through the GitHub Action, and over the wire at POST /api/v1/check. Milliseconds, before any GPU is billed.

warn performance R35
TriggerTotal fp16 K/V cache across all attention layers (GQA-aware: counts numKVHeads, skips MLA) exceeds 4 GB for a single 8,192-token sequence.
WhyThat much cache for ONE sequence is gone before weights or activations load; on a 24 GB GPU it caps concurrency at a handful of requests. Raise the GQA ratio, switch to MLA, reduce depth/width, or accept a shorter serving context.
SourceSame per-token KV math as R31 and the serving calculator, applied as an absolute budget instead of a pattern.

Why it is not a lint you can ignore

A structural mistake does not fail at review time and it does not fail at import time. It fails when the module is constructed on the training node, after the job was queued and the dataset was downloaded. That is why this runs before the spend and not after it.
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Every check

41 structural checks: 6 guardrail gates and 35 architecture advisor rules. See the full catalogue.

← R34 LM head width disagrees with embedding vocab