Skip to content
Signalcrest
Back to feed
githubai

project-maya — Project Maya - run GLM-5.3-Flash (321B MoE) privately on your own GPU(s), from one card to 16, NVIDIA or AMD, Linux or Window

Run a 321B MoE LLM locally for private inference on NVIDIA or AMD GPUs.

Steady
Signal score
7
Trajectory
↓ Cooling
7-day est. ~0

Why this scored 7

every term, weighted
Velocity+0.6 / 40

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

Acceleration+12.5 / 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+4.2 / 10

Decays to zero over 14 days

Saturation penalty−10.2 / 30

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

Composite7.1

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

low confidence · estimate, not a guarantee

7-day

~0

range 0–12

14-day

~0

range 0–14

30-day

~0

range 0–19

Signal history

7-day window (free)
015

projected trajectory (estimate, not a guarantee)

Entities

projectmayaglm5.3-flashnvidia
Embed a live signal badge
Signalcrest signal badge
[![Signalcrest signal](https://www.signalcrest.app/api/badge/gh%3A1407997858)](https://www.signalcrest.app/topic/gh%3A1407997858)

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