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Gemma 4 on Amazon SageMaker: QAT Weights Decode 2.05x Faster Than bf16 on One L4

Gemma 4 quantized runs 2.05× faster on SageMaker L4, lowering inference latency and cost.

Cooling
Signal score
11
as of 1d ago
Trajectory
⏳ Too early
needs a few more snapshots

Why this scored 11

every term, weighted
Velocity+0.0 / 40

Engagement gained per hour since the last capture, against the fastest item on its own source

Acceleration+1.1 / 25

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25

How many independent communities are talking about the same entity

Recency+9.9 / 10

Decays to zero over 14 days

Saturation penalty−0.0 / 30

Subtracted once something is big and old — we rank what's next, not what's peaked

Composite10.9

Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On a topic's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology

Signal history

7-day window (free)
1175

Entities

gemma4sagemakernvidia l4
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Drop this in a README or blog post — it updates automatically as the score moves.