# $PI Social Sentiment & Intelligence — 2026-09-17 14:30 UTC

> **Asset:** $PI  
> **Momentum Status:** Cooling Down  
> **Timestamp:** 2026-09-17 14:30 UTC (2026-09-17T14:30:00Z)  
> **Canonical URL:** https://cryptitalk.com/2026-09-17-14-30/crypto/PI  
> **Overview Brief:** https://cryptitalk.com/2026-09-17-14-30/crypto.md  

---

## 10-Minute Social Metrics
- **Posts Analyzed:** 2
- **Total Impressions:** 101
- **Likes:** 5
- **Retweets:** 0
- **Comments:** 3

---


## Momentum & Sentiment Analysis
Total Engagement - Comments: 3, Retweets: 0, Likes: 5, Impressions: 101


---

## Cited Community Posts & Evidence


### Post #1 by @spheron
> **Author:** [@spheron](https://x.com/spheron)  
> **Metrics:** 0 likes · 0 retweets · 0 comments · 323 views  


> **Source Link:** [https://x.com/spheron/status/2100594068841734597](https://x.com/spheron/status/2100594068841734597)  


> **Visual Context:** A comparison chart titled 'H200 vs H100 (Llama 2 70B)' showing throughput: H100 at 22,290 tokens/sec and H200 at 31,712 tokens/sec, marking it as 42% faster, by Spheron Network.  

> 
> "The arithmetic that decides your GPU shopping list: a 70B model at FP16 needs about 140GB of VRAM. Quantization cuts that 2-4x. Every 1,000 tokens of context adds roughly 0.5-1GB of KV cache for a 7B model, scaling linearly with size.

Budget 20-30% overhead on top of the base"


### Post #2 by @AkiraRyukyu
> **Author:** [@AkiraRyukyu](https://x.com/AkiraRyukyu)  
> **Metrics:** 0 likes · 0 retweets · 0 comments · 5 views  


> **Source Link:** [https://x.com/AkiraRyukyu/status/2100593112443953390](https://x.com/AkiraRyukyu/status/2100593112443953390)  


> 
> "the onchain receipts make these claims way easier to verify firsthand"




---


## Contributing Accounts

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

- `@kaizo2489` (https://x.com/kaizo2489)