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$MFT

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Snapshot Window: 2026-09-02 22:20 UTC · ← Back to Crypto Overview

Tracked Posts
7
Total Impressions
814
Total Likes
24
Retweets & Quotes
5
Comments
4

Social Momentum Summary

Total Engagement - Comments: 4, Retweets: 5, Likes: 24, Impressions: 814

Verbatim Community Citations & Social Evidence 7 source posts analyzed

@MSBIntel

BREAKING: Avalanche contract deployments surged 204% to 1.9 million over the past 30 days.

@Headmetax

$ETH is hovering around the $2.4K–$2.5K zone, with the market under pressure as rising oil prices, Treasury yields and geopolitical tensions keep risk appetite cautious. The bullish angle: U.S. spot ETH ETFs recorded $10.95M in net inflows on Sept. 1, extending the streak to 12

@MSBIntel

DeFi generated $79 million in fees in 24 hours, $512 million over seven days and $1.89 billion over 30 days. That 30 day pace annualises to $23.00 billion. Source: DefiLlama.

@gmekhail

Thank you @UTXOmgmt @HashKeyGroup @Anchorage @Metaplanet . Grateful for our members and the team. Cheers.

@reddit

NeoxEX (aka Neoxa.exchange) exchange is a scam. Deposited $500 in BTC, funds vanished. Avoid. Suggested for you

@aufsol

Lmfao @vladtenev can do the funniest thing, only $160k for universal mog atm

A neon green and black graphic with three parallelogram-shaped banners reading "Move on bro. Trenches are now on Robinhood" — a humorous jab at Robinhood making "trenches" (risky meme stock trading) accessible to retail investors, tying into the post mocking the accessibility of volatile trading for as little as $160k.

AI visual note: A neon green and black graphic with three parallelogram-shaped banners reading "Move on bro. Trenches are now on Robinhood" — a humorous jab at Robinhood making "trenches" (risky meme stock trading) accessible to retail investors, tying into the post mocking the accessibility of volatile trading for as little as $160k.

@IOHK_Charles

That 28 billion dollar Wang is starting to pay off

A benchmark comparison table showing performance scores across four AI models—Muse Spark 1.3 (max), Muse Spark 1.2 (high), GPT 5.6 Sol (max), and Opus 5 (max)—across categories including Agent (GDPVal-AA v2, JobBench, OSWorld 2.0, DeepResearchQA, Agentic IF Index, AutomationBench), Long context (MRCR), and Coding (SWEAtlas CodeBase QnA, Terminal-Bench 2.1). Notably, Opus 5 leads in most agentic benchmarks with scores like 1824 on GDPVal-AA v2 and 68.3 on OSWorld 2.0, while Muse Spark 1.3 outperforms in long context retrieval (98.5/98.1 on MRCR) and terminal coding (88.8 on Terminal-Bench). The image relates to the post by showcasing Meta's "Muse Spark" models—likely referencing Mark Zuckerberg's massive

AI visual note: A benchmark comparison table showing performance scores across four AI models—Muse Spark 1.3 (max), Muse Spark 1.2 (high), GPT 5.6 Sol (max), and Opus 5 (max)—across categories including Agent (GDPVal-AA v2, JobBench, OSWorld 2.0, DeepResearchQA, Agentic IF Index, AutomationBench), Long context (MRCR), and Coding (SWEAtlas CodeBase QnA, Terminal-Bench 2.1). Notably, Opus 5 leads in most agentic benchmarks with scores like 1824 on GDPVal-AA v2 and 68.3 on OSWorld 2.0, while Muse Spark 1.3 outperforms in long context retrieval (98.5/98.1 on MRCR) and terminal coding (88.8 on Terminal-Bench). The image relates to the post by showcasing Meta's "Muse Spark" models—likely referencing Mark Zuckerberg's massive

Contributing Voices for $MFT

@MemeForTrees