# $STRX Social Sentiment & Intelligence — 2026-08-11 08:40 UTC

> **Asset:** $STRX  
> **Momentum Status:** Stable  
> **Timestamp:** 2026-08-11 08:40 UTC (2026-08-11T08:40:00Z)  
> **Canonical URL:** https://cryptitalk.com/2026-08-11-08-40/crypto/STRX  
> **Overview Brief:** https://cryptitalk.com/2026-08-11-08-40/crypto.md  

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## 10-Minute Social Metrics
- **Posts Analyzed:** 1
- **Total Impressions:** 3.1K
- **Likes:** 101
- **Retweets:** 20
- **Comments:** 56

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## Momentum & Sentiment Analysis
Total Engagement - Comments: 56, Retweets: 20, Likes: 101, Impressions: 3099


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## Cited Community Posts & Evidence


### Post #1 by @ionet
> **Author:** [@ionet](https://x.com/ionet)  
> **Metrics:** 1 likes · 0 retweets · 0 comments · 1.5K views  


> **Source Link:** [https://x.com/ionet/status/2087097437869510900](https://x.com/ionet/status/2087097437869510900)  


> **Visual Context:** "LLM Fine-Tuning Budget Guide" by io.net, featuring a 3D stack of AI-themed blocks, illustrating the cost comparison between expensive API fine-tuning and affordable decentralized GPU fine-tuning for large language models.  

> 
> "Fine-tuning GPT-4o via API: ~$640 for a 50K-example run.

Fine-tuning Llama 3.1 70B on 
io.net: ~$26. 

Same task, but with full weight ownership, no API dependency, and 25x cheaper.

Most teams don't need a frontier API. They need the right open-source model on"




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## Contributing Accounts

- `@Itxzain189911` (https://x.com/Itxzain189911)