TokenInsight Report: MEXC Ranks No. 1 Globally in Silver Futures Liquidity, Leading Across Multiple Metrics

VICTORIA, Seychelles, June 1, 2026 /PRNewswire/ -- TokenInsight recently released its Crypto Exchange Liquidity Report, providing a systematic assessment of liquidity performance across eight major global crypto exchanges based on order book depth, trading slippage, and bid-ask spread. According to the report, MEXC, a pioneer in 0-fee digital asset trading, ranked among the top performers across multiple key liquidity metrics, including SILVER(XAG) Futures slippage, bid-ask spread, and ETH Futures slippage. Notably, MEXC ranked first across all measured indicators for silver Futures.

Silver Futures rank first across all metrics: lowest slippage and tightest spread
In the precious metals Futures market, MEXC also demonstrated strong liquidity advantages. According to the report, MEXC recorded the lowest slippage across all SILVER(XAG) Futures measurements, with median slippage of just 0.019% for $500K sell orders and 0.035% for $1M sell orders, outperforming other major exchanges overall.

Meanwhile, MEXC's XAG Futures bid-ask spread ranked as the tightest at 1.196 bps, clearly ahead of the concentrated range of 1.315 to 1.351 bps seen among other exchanges. The dual advantage in both slippage and spread reflects MEXC's more competitive quote quality and execution efficiency in the SILVER(XAG) Futures market.

ETH Futures slippage leads across all order sizes
The report also shows that MEXC led across ETH Futures slippage metrics. In the $1M sell order test, MEXC recorded median slippage of only 0.015%, with P90 slippage at 0.020%. In the $5M sell order test, median slippage stood at 0.050%, with P90 slippage at 0.056%. This indicates that during the sample period, MEXC demonstrated strong order absorption capacity and stable execution performance in large-size ETH Futures trading scenarios.

Precious metals Futures order book depth ranks third overall
In addition to slippage and spread, MEXC also performed strongly in precious metals Futures order book depth. According to the report, MEXC recorded cumulative depth of $4.3 million within the 0.1% price range and $8.9 million within the 0.3% price range, ranking third overall. Sufficient order book depth helps reduce the price impact of large orders and provides users with a more stable trading execution environment.

Overall, low slippage, tight spreads, and sufficient order book depth are key foundations of a strong Futures trading experience. Looking ahead, MEXC will continue to enhance liquidity performance and create infinite opportunities for users worldwide.

Full report: TokenInsight Crypto Exchange Liquidity Report, May 2026

About MEXC
MEXC is the world's fastest-growing cryptocurrency exchange, trusted by more than 40 million users across 170+ markets. Built on a user-first philosophy, MEXC offers industry-leading 0-fee trading and access to over 3,000 digital assets. As the Gateway to Infinite Opportunities, MEXC provides a single platform where users can easily trade cryptocurrencies alongside tokenized assets, including stocks, ETFs, commodities, and precious metals.
MEXC Official Website｜ X ｜ Telegram ｜How to Sign Up on MEXC

 

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TokenInsight Report: MEXC Ranks No. 1 Globally in Silver Futures Liquidity, Leading Across Multiple Metrics

TokenInsight Report: MEXC Ranks No. 1 Globally in Silver Futures Liquidity, Leading Across Multiple Metrics

SINGAPORE, Aug. 2, 2026 /PRNewswire/ -- Artificial intelligence has transformed academic writing. Today, researchers can summarize hundreds of papers, generate literature reviews, and even draft complete manuscripts in minutes. But as AI becomes an indispensable research tool, a new challenge is emerging: many AI-generated citations cannot be trusted.

Fabricated references, incorrect author names, invalid DOIs, and nonexistent journal articles have become one of the most widely recognized limitations of large language models. While AI dramatically improves writing efficiency, unreliable citations threaten the credibility of research itself.

Wispaper, an AI-powered academic research platform, believes the next generation of academic AI must solve this trust problem—not simply produce more text.

Today, the company announced its next-generation AI Research Agent, together with True Cite, a citation verification system designed to help researchers build papers on authentic, verifiable academic sources instead of AI-generated references.

Unlike conventional AI writing assistants that focus on content generation, Wispaper is built around the complete research process. The platform helps researchers discover research gaps, explore hypotheses, organize literature, and develop stronger scientific arguments before writing begins. Throughout this workflow, True Cite enables users to verify references against real academic publications, helping reduce the risk of citation hallucinations while improving research reliability.

"Everyone is talking about how fast AI can write," said a Wispaper spokesperson. "We believe the more important question is whether researchers can trust what AI produces. Scientific progress depends on evidence, and evidence begins with trustworthy sources."

As AI adoption accelerates across universities and research institutions, expectations for academic AI are evolving. Researchers are no longer looking only for writing assistants—they need AI systems that support scientific reasoning while maintaining academic integrity.

By combining reasoning-first research workflows with citation verification, Wispaper aims to redefine the role of AI in academia—from a text generator to a trusted research partner.

About WisPaper

WisPaper is an AI-powered academic research agent designed as a full-stack research accelerator. It supports literature retrieval, analysis, experiment design, execution, and paper writing within a unified workflow, helping researchers manage complex scientific tasks more efficiently across disciplines. For more information, visit https://wispaper.ai/?utm_source=news.

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AI Can Write Research Papers. But Can Researchers Trust the Citations? Wispaper Says That's the Next Challenge for Academic AI