Target
Bound or compress KV memory for long local contexts.
Failure this recipe addresses
KV cache growth, not model weights, is the measured memory blocker.
Data contract
Long-context replay prompts with cached-forward quality checks.
Method or policy
Retain attention sinks/window tokens or quantize KV groups, then replay identical continuations.
Evaluation contract
Cache bytes and trajectory/perplexity parity versus full KV.
- long-context recall
- greedy prefix match
- throughput
- storage packing
- composition
Budget and stop rule
Existing smokes are closed; new work requires a long-context product blocker.
Stop if memory savings lack a packed representation or quality gate.
Decision rule
Keep as an opt-in long-context lever until quality and composition gates pass.
Learning exercise
Calculate full, windowed, int8, and int4 KV bytes for one model/context.
Choose between eviction and quantization from the actual context failure mode.
How to read this dossier
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Status and disposition describe what PostTrainLLM retained when this record was indexed. They are not a live product promise, a newly run benchmark, or permission to restart historical work. Unknown or unmeasured fields remain unknown rather than being treated as zero.
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Source provenance
The normalized record comes from docs/recipes/registry.json. The links below are the tracked evidence and explanatory sources preserved with the record.