# $XEC Social Sentiment & Intelligence — 2026-09-24 02:10 UTC

> **Asset:** $XEC  
> **Momentum Status:** Trending Up  
> **Timestamp:** 2026-09-24 02:10 UTC (2026-09-24T02:10:00Z)  
> **Canonical URL:** https://cryptitalk.com/2026-09-24-02-10/crypto/XEC  
> **Overview Brief:** https://cryptitalk.com/2026-09-24-02-10/crypto.md  

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## 10-Minute Social Metrics
- **Posts Analyzed:** 1
- **Total Impressions:** 87
- **Likes:** 1
- **Retweets:** 0
- **Comments:** 0

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## Momentum & Sentiment Analysis
Total Engagement - Comments: 0, Retweets: 0, Likes: 1, Impressions: 87


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## Cited Community Posts & Evidence


### Post #1 by @0xCVYH
> **Author:** [@0xCVYH](https://x.com/0xCVYH)  
> **Metrics:** 29 likes · 2 retweets · 2 comments · 2.3K views  


> **Source Link:** [https://x.com/0xCVYH/status/2102922528075464783](https://x.com/0xCVYH/status/2102922528075464783)  


> **Visual Context:** The image is a bar chart titled "Same items, same scoring" comparing accuracy (%) across eight benchmarks for four models: Eikos-27B (orange), Eikos-4B (light yellow), Jev (light blue), and Laya (dark blue). Key results shown include Eikos-27B achieving 82.9% on JevBench-hard, 83.4% on DecisionBench, and 95.3% on Compositional rules, generally outperforming or matching Jev across categories while Laya scores notably lower on most benchmarks (e.g., 36.1% on DecisionBench, 42.9% on Compositional rules). The chart visually reinforces the post's claim that Eikos (open-source from MIT) achieves superior or comparable performance to Jev on the same evaluation items, highlighting strengths in decision-making benchmarks with both 27B and 4B parameter versions.  

> 
> "Eikos is open (MIT).

Decision models (System One) of 4B and 27B: decide in a single pass and state the probability of each option.

• 27B: 82.9% on JevBench hard (Jev: 73.0)
• 2.4% error with ≥90% certainty (Jev: 5.9%)
• 64k context

Same items, same score: 8 batteries"




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## Contributing Accounts

- `@EricLima81` (https://x.com/EricLima81)