# $WIRE Social Sentiment & Intelligence — 2026-08-08 18:20 UTC

> **Asset:** $WIRE  
> **Momentum Status:** Trending Up  
> **Timestamp:** 2026-08-08 18:20 UTC (2026-08-08T18:20:00Z)  
> **Canonical URL:** https://cryptitalk.com/2026-08-08-18-20/crypto/WIRE  
> **Overview Brief:** https://cryptitalk.com/2026-08-08-18-20/crypto.md  

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## 10-Minute Social Metrics
- **Posts Analyzed:** 1
- **Total Impressions:** 753
- **Likes:** 9
- **Retweets:** 2
- **Comments:** 3

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## Momentum & Sentiment Analysis
Total Engagement - Comments: 3, Retweets: 2, Likes: 9, Impressions: 753


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## Cited Community Posts & Evidence


### Post #1 by @octralabs
> **Author:** [@octralabs](https://x.com/octralabs)  
> **Metrics:** 71 likes · 18 retweets · 9 comments · 5.5K views  


> **Source Link:** [https://x.com/octralabs/status/2085737948864025022](https://x.com/octralabs/status/2085737948864025022)  


> **Visual Context:** A screenshot of a web-based LLM interface called "smolLM2-360M-instruct" running locally via octra webcli, displaying an active chat where a user asked "hi, how are you? how can you help me?" and received a friendly AI response offering assistance with questions and concerns. The interface shows technical details like the token count (32), context size, and model parameters, demonstrating the onchain LLM inference capability described in the post.  

> 
> "an early demo of onchain LLM inference inside an octra circle (unencrypted) is now available through webcli.

to test, install webcli, run ./octra_wallet and navigate to:
http://127.0.0.1:8420/circles.html?uri=oct://oct99BWHFpV5r54DXKc2FhsBmZEaS6Q8zvCQrHRgXUcK4Fk%2Findex.html"




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## Contributing Accounts

- `@wirebotRH` (https://x.com/wirebotRH)