diff --git a/content/essays/verified-inference/index.md b/content/essays/verified-inference/index.md index 5a91eb9..f89fda6 100644 --- a/content/essays/verified-inference/index.md +++ b/content/essays/verified-inference/index.md @@ -199,11 +199,10 @@ targets. One morning and about eleven dollars of GPU time later: - the extracted Maverick manifest reported **109,273,513 witness rows, against the production run's measured 109.27 M** — the profiler reproducing reality, not merely its own model of it; -- the first cost bracket priced on measured Blackwell constants put the full - Maverick proof at a **376-second floor** on one B200 — roughly 28× the - development box, tracking the measured bandwidth ratio almost exactly, - which is what the cost model's scaling story says should happen when the - dominant terms ride memory bandwidth. +- the cost bracket priced on measured Blackwell constants puts the + routed-projected Maverick proof at S=1000 at a **254-second floor** on one + B200, the dominant terms riding memory bandwidth and tracking that 29× + ratio — which is what the cost model's scaling story says should happen. I also corrected the cost model's RMSNorm row to the wrap-free bracket constants, bringing it into line with the paper's own analysis. @@ -264,12 +263,18 @@ context length, and mixture-of-experts breadth — the dimensions along which a single box runs out first. The honest projection carries the same bracket as everything else here. The -anchor is a **376-second floor for the full Maverick proof on one B200**: a -floor, not today's code, and it assumes the reorganization the cost model -already itemizes. Distributing that across 2–8 devices puts a 400B proof in the -low minutes if the partition scales cleanly, and under a minute at the -optimistic end. Both numbers are projections from a model validated against one -archived run and one live machine — good enough to plan against, not yet a +anchor is a **254-second floor for the routed-projected Maverick proof at +S=1000 on one B200**: a floor, not today's code, and it assumes the +reorganization the cost model already itemizes. On that same model, four-way +sharding predicts **3.95× of a possible 4×**, with interconnect traffic +negligible — near-linear scaling is plausible here only because the traffic +model was corrected, which makes this the direct payoff of the retraction +above. Distributing across 2–8 devices puts a 400B proof in the low minutes, +and under a minute at the optimistic end. + +Every figure in that paragraph is a prediction priced on measured constants, +not a multi-GPU measurement. The model behind them has been validated against +one archived run and one live machine — good enough to plan against, not yet a measurement. Beyond that, fleets of 64–128 GPUs are what an order-of-magnitude larger model