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The Last Pivot: Why Quality Gates Killed My Final KV-Cache Speedup

DEV Community·Alankrit Verma·7 months ago
#K19A8mYM
#pivot#speed#machinelearning#ai#quality
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I wanted to answer one question:

After packed-codebook TurboQuant failed, was there still a credible latency path?

The short answer:

there was a real speed ceiling, but no stable quality-preserving implementation path.

TL;DR

Hardware-friendly int4 K/V passed byte gates but failed real-KV logit quality.

Qwen2.5-7B work reduction had a real speed ceiling: p_attn=0.334 , with 1.20x to 1.21x projected speedup at 5% selector overhead.

Oracle quality failed anyway: no implementable selector passed all 4 decode steps.

The lesson was strict: a speed ceiling is only permission to run a quality gate, not permission to implement.

Evidence

I put the detailed benchmark notes in the public evidence repo:

Results ledger: https://github.com/AlankritVerma01/turboquant-kv-cache-evidence/blob/main/results-ledger.md

Hardware-friendly int4 K/V quality probe: https://github.com/AlankritVerma01/turboquant-kv-cache-evidence/blob/main/evidence/benchmark-summaries/hfkv-quality-k0-prep-summary.md

Work-reduction speed and…

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