Is Speculative Decoding's Speedup a Hardware Problem or a Model Problem?
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A follow-up/sub-part to Part 3 of the LLM inference internals series. Part 3 built sampling-mode speculative decoding with KV caching on both the draft and verifier sides, and it worked correctly, but the speedup it delivered didn't match expectations set by the paper. This post is the record of chasing that gap: every hypothesis tested, which ones were wrong, and what the real answer turned out to be. Starting Point: It's Slower, Not Faster The first full gamma sweep, on an open-ended,…
1Key Takeaways
- A follow-up/sub-part to Part 3 of the LLM inference internals series.
- Part 3 built sampling-mode speculative decoding with KV caching on both the draft and verifier sides, and it worked correctly, but the speedup it delivered didn't match expectations set by the paper.
- This post is the record of chasing that gap: every hypothesis tested, which ones were wrong, and what the real answer turned out to be.
- Starting Point: It's Slower, Not Faster The first full gamma sweep, on an open-ended,….
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that a follow-up/sub-part to Part 3 of the LLM inference internals series.
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