Search results for "COST"
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03:22

NAWS (NAWS.AI) up 34.92% in 24 hours

Gate News update: On April 28, according to Gate market data, as of the time of publication, NAWS (NAWS.AI) is trading at $0.00071. It is up 34.92% over the past 24 hours, reaching a high of $0.000713 and a low of $0.000524. The 24-hour trading volume is $2817.12. The current market cap is approximately $1.4145 million. NAWS is a no-code platform for users to sell Web2, Web3 content, and DePIN credentials. The P2P crypto payment system uses a DEX AI aggregator for secure, low-cost payments, allowing users to choose tokens for trading. Foundations and projects can use their tokens to grow their ecosystem. NAWS Quest rewards user activity through points from redeemable tokens.
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NAWS16.15%
05:04

PEPE(PEPE)up 2.98% over 24 hours

Gate News 消息,4 月 27 日,据 Gate 行情显示,截至发稿时,PEPE(PEPE)现报 0.00000398 美元,24 小时内上涨 2.98%,最高触及 0.00000402 美元,最低回落至 0.00000384 美元,24 小时交易量达 11.03M美元。当前市值约为 1.67B美元。 PEPE is a meme coin. PEPE近期 important news: 1️⃣ **Top whales continue to add positions** A certain top whale, after an 8-month gap, bought another 1.67B PEPE tokens again, costing approximately $3.08 million. After averaging down, its average holding price dropped to about $0.0000074286. This move reflects that large-position holders continue to see the long-term value of PEPE. Although it is still in an unrealized loss at the moment, by taking a staged approach it reduces the cost of holdings, showing bullish confidence. 2️⃣ **Top profit whales still hold large positions** The PEPE whale dimethyltryptamine.eth has accumulated profits of $11.9 million in this coin, and still holds $800B in positions at present. This indicates that the core profit-takers have not cashed out significantly, and instead chose to keep holding, reflecting a long-term bullish stance. 3️⃣ **Ecosystem-related parties diversify their allocations** A related address with fund flows with the PEPE whale recently spent $245k to purchase other tokens, ASTEROID. This suggests that large funds are making multi-chain or cross-project investment allocations within the PEPE ecosystem, reflecting broad market optimism from active capital. This news is not investment advice. Be mindful of market volatility risks when investing.
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PEPE1.1%
04:54

Perplexity Discloses Web Search Agent Post-Training Method; Qwen3.5-Based Model Outperforms GPT-5.4 on Accuracy and Cost

Perplexity uses SFT followed by RL with Qwen3.5 models, leveraging a multi-hop QA dataset and rubric checks to boost search accuracy and efficiency, achieving best-in-class FRAMES performance. Abstract: Perplexity's post-training workflow for web-search agents combines supervised fine-tuning (SFT) to enforce instruction-following and language consistency with online reinforcement learning (RL) via the GRPO algorithm. The RL stage uses a proprietary multi-hop verifiable QA dataset and rubric-based conversational data to prevent SFT drift, with reward gating and within-group efficiency penalties. Evaluation shows Qwen3.5-397B-SFT-RL achieving top FRAMES performance, 57.3% accuracy with a single tool call and 73.9% with four calls at $0.02 per query, outperforming GPT-5.4 and Claude Sonnet 4.6 on these metrics. Pricing is API-based and excludes caching.
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