Perle
PRL#883Solana$0.1167+4.22%
Vertrag
PERLEQKU…fs6pDsPerle (PRL) notiert aktuell bei $0.1167, ein Plus von 4.22% in den letzten 24 Stunden, und belegt Rang 883 nach Marktkapitalisierung. Auf Wochensicht liegt der Kurs 2.73% im Minus. Damit steht Perle 75.06% unter dem Allzeithoch von $0.4678 vom 19. August 2026. Das 24-Stunden-Handelsvolumen beträgt 1,88 Mio. $.
Lädt...Kursperformance
1H
+0.07%
1T
+4.22%
1W
-2.73%
1M
-32.86%
1J
—
Marktdaten
Preis
$0.1167
Marktkapitalisierung
$20,416,441.00
24h Volumen
$1,876,430.00
24h Hoch
$0.1192
24h Tief
$0.112
Umlaufmenge
175.00M
Gesamtangebot
1.00B
Max. Angebot
1.00B
Fully Diluted Bewertung
$116,665,374.00
Allzeithoch
$0.4678
-75.06% vom ATH · 8/19/2026
Allzeittief
$0.1046
+11.59% vom ATL · 9/15/2026
Zuletzt aktualisiert
9/30/2026, 2:34:40 AM
Märkte
| # | Börse | Paar | Preis | 24h Volumen | Spread | |
|---|---|---|---|---|---|---|
| 1 | PRL/USDT | $0.1168 | $664,691.00 | 0.36% | Handeln | |
| 2 | PRL/KRW | $0.1168 | $529,632.00 | 0.63% | Handeln | |
| 3 | PRL/KRW | $0.116 | $108,893.00 | 0.64% | Handeln | |
| 4 | PRL/USDT | $0.1165 | $89,634.00 | 0.17% | Handeln | |
| 5 | PRL/USDT | $0.1167 | $68,836.00 | 0.34% | Handeln | |
| 6 | PRL/USDT | $0.1166 | $60,819.00 | 1.02% | Handeln | |
| 7 | PRL/USDT | $0.1166 | $58,102.00 | 0.26% | Handeln | |
| 8 | PRL/USDT | $0.1168 | $55,200.00 | 0.34% | Handeln | |
| 9 | PRL/USDC | $0.1166 | $54,832.00 | 0.68% | Handeln | |
| 10 | PRL/USDT | $0.1166 | $48,355.00 | 0.27% | Handeln |
1
LBankPRL/USDT
$0.11682
UpbitPRL/KRW
$0.11683
BithumbPRL/KRW
$0.1164
GatePRL/USDT
$0.11655
ToobitPRL/USDT
$0.11676
CoinWPRL/USDT
$0.11667
MEXCPRL/USDT
$0.11668
BingXPRL/USDT
$0.11689
MEXCPRL/USDC
$0.116610
BloFinPRL/USDT
$0.11661 / 2
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Über Perle
Perle Labs is a web3-powered AI platform on Solana that connects verified experts with enterprises and research teams to train and improve AI models. Professionals, researchers, and domain specialists earn rewards and build on-chain reputations by completing high-quality data annotation and validation tasks.
Pain points the project addresses includes:
Human Data Bottlenecks: Continuous need for high-volume, high-quality data annotation, evaluation, and RLHF, but existing pipelines lack scalability.
Low-Quality Feedback: Reliance on generic labor pools without domain expertise, leading to noisy signals and degraded AI accuracy.
Lack of Verifiability: Opaque processes without audit trails for contributor performance and quality.