wladimiravila/esp32s3-distributed-ai
Distributed 56M-parameter LLM inference across 3 ESP32-S3 boards via ESP-NOW , Split-PLE + KV cache, fully offline.
118
Stars
15
Forks
40.7
Radar Score
Rising
Momentum
Scoring Breakdown
Impact25.1
Velocity47.0
Health56.9
Growth Metrics
7-Day Stars
+0
30-Day Stars
+0
Acceleration
x
Language
C
Why it ranks
Steady growth — consistently collecting stars and contributors.
LLM Frameworks · inference engineTop 59% globally
Popular Alternatives & Competitors
Top projects in the same category (LLM Frameworks) — compare side by side.
🛡️ Enterprise Readiness & Commercial Safety
Organic Growth
88%
High Confidence
License
Unlicensed / Custom
Review license terms carefully before commercial adoption.
Health Grade
A
Based on maintenance, issue response, and release cadence.
Radar Score
40.7
Composite of Impact, Velocity, and Health.
Disclaimer: This is an automated heuristic assessment based on public GitHub signals. Always perform your own security audit, dependency review, and legal compliance check before production deployment.
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