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empero-ai/Qwen3.8-27B-Ridge-GGUF (image-text-to-text)

Quantized Qwen 3.8B model in GGUF format speeds up image-text inference.

Steady

21

signal score

as of 2d ago

🔗 3

sources · qwen3.8-27b

Accelerating

7-day est. ~28

Why this scored 21

every term, weighted
Velocity+0.0 / 40 max

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

Acceleration+11.7 / 25 max

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

Cross-source spread+16.7 / 25 max

How many independent communities are talking about the same entity

Recency+3.1 / 10 max

Decays to zero over 14 days

Saturation penalty10.8 / 30 max

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

Composite20.6

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

Outlook

medium confidence · estimate, not a guarantee

7-day

~28

range 1640

14-day

~30

range 1544

30-day

~31

range 1250

Signal history

7-day window (free)

— — projected trajectory (estimate, not a guarantee)

Entities

qwen3.8-27b
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