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Top 5 Layer 1 Chains By Active Users (Q1 2026) 🔹 $BNB Chain leads Layer 1 networks with 4.5M daily active users, followed by $TRX at 3.2M, while $NEAR and $SOL stay neck-and-neck in the mid-tier. 🔹 Will these rankings shift as user adoption accelerates across L1 ecosystems in Q1 2026? #CoinPedia# #CryptoNews# #Blockchain# #CryptoMarket#
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Announcing the Artificial Analysis Coding Agent Index! Our new coding agent benchmarks measure how combinations of agent harnesses and models perform on 3 leading benchmarks, token usage, cost and more When developers use AI to code they’re choosing a model, but also pairing it with a specific harness. It makes sense to benchmark that combination to understand and compare performance. The Artificial Analysis Coding Agent Index includes 3 leading benchmarks that represent a broad spectrum of coding agent use: ➤ SWE-Bench-Pro-Hard-AA, 150 realistic coding tasks that frontier models struggle with, sampled from Scale AI’s SWE-Bench Pro ➤ Terminal-Bench v2, 84 agentic terminal tasks from the Laude Institute and that range from system administration and cryptography to machine learning. 5 tasks were filtered due to environment incompatibility ➤ SWE-Atlas-QnA, 124 technical questions developed by Scale AI about how code behaves, root causes of issues, and more, requiring agents to explore codebases and give text answers Analysis of results: ➤ Opus 4.7 and GPT-5.5 lead the Index: Opus 4.7 in Cursor CLI scores 61, followed closely by GPT-5.5 in Codex and Opus 4.7 in Claude Code at 60. GPT-5.5 in Cursor CLI follows at 58. ➤ Open weights models are competitive, but still trail the leaders: GLM-5.1 in Claude Code is the top open-weight result at 53, followed by Kimi K2.6 and DeepSeek V4 Pro in Claude Code at 50. These are strong results, but still meaningfully behind the top proprietary models. ➤ Gemini 3.1 Pro in Gemini CLI underperforms: Gemini 3.1 Pro in Gemini CLI scores 43, well below where Gemini 3.1 Pro sits on our Intelligence Index, highlighting that Gemini’s performance in Gemini CLI remains a relative weak spot for Google’s offering. ➤ Cost per task (API token pricing) varies >30x: Composer 2 in Cursor CLI is cheapest at $0.07/task, followed by DeepSeek V4 Pro in Claude Code at $0.35/task and Kimi K2.6 in Claude Code at $0.76/task. At the high end, GPT-5.5 in Codex costs $2.21/task, while GLM-5.1 in Claude Code costs $2.26/task. For both models this was contributed to by high token usage, and in GPT-5.5’s case by a relatively higher per token cost. ➤ Token usage varies >3x: GLM-5.1 in Claude Code uses the most tokens at 4.8M/task, followed by Kimi K2.6 at 3.7M/task and DeepSeek V4 Pro at 3.5M/task. GPT-5.5 in Codex uses 2.8M tokens/task, substantially more than Opus 4.7 in Claude Code at 1.7M/task. In GLM-5.1’s case, higher token usage, cost and execution time were partly driven by the model entering loops on some tasks. ➤ Cache hit rates remain high but vary materially: Cache hit rates range from 80% to 96% across combinations. Provider routing, harness prompt structure and cache behavior can materially change the economics of running the same model given cached inputs are typically <50% the API price of regular input tokens. ➤ Time per task varies >7x: Opus 4.7 in Claude Code is fastest at ~6 minutes/task, while Kimi K2.6 in Claude Code is slowest at ~40 minutes/task. This is contributed to by differences in average turns per task, token usage and API serving speed. Opus 4.7 had materially lower amount of turns to complete a task than all other models while Kimi K2.6 had the most. ➤ Cursor made real progress with Composer 2: Composer 2 in Cursor CLI scores 48, near the leading open-weight model results, while being the cheapest combination measured at $0.07/task. Cursor has stated Composer 2 is built from Kimi K2.5, showcasing they have made substantial post-training gains. This is just the start. We are planning to add additional agents (both harnesses and models). Let us know what you would like to see added next.
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2026 年了,BTC 周末做空波动率还能赚钱吗? @cryptarbitrage 去年在 Deribit Insights 上发表了《再谈 BTC 周末做空波动率策略》,他在文中介绍了一个在 ETF 上市后依然有效的简单策略: 周五 16:00 UTC 卖出一组周日 08:00 UTC 到期、35 delta 的 BTC 宽跨式,持有到期不做对冲。 这个策略在 2024 年 9 月至 2025 年 4 月的样本期取得了年化收益 41%、最大回撤 4.5%、夏普 5.31 的成绩(含面值万 3 手续费 + 5% 报价滑点)。原文作者甚至花了大量篇幅解释这是做空波动率策略在短窗口的超常发挥,不可以当做常态处理。 一年过去了,这个策略在公开发表后是否还存在超额收益呢?我们通过正在内测的格致期权回测功能,将策略表现更新至 2026 年 5 月 8 日,结果发现:周末做空波动率策略虽然经历了 2025 年 10 月和 2026 年 1 月两次闪崩,但夏普依然稳定在 2.24,最大回撤为 5.2% 周末效应的风险溢价没因为策略公开就消失,两次闪崩属于做空波动率的常态尾部风险,当前市场的隐含波动率整体降低,单笔盈利缩水,总体表现打了折。
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$PROS Launched, Now the Next Phase Starts Pharos is excited to announce that following the $PROS launch, Pharos has met the investment benchmark set during the strategic agreement with GCL new energy! Soon the two parties will start the first phase of the equitity-to-token swap. Final regulatory procedures are currently being executed Based on this milestone, Pharos and GCL New Energy will extend the partnership through: - Deep Integration of web2 industrial assets and web3 Infrastructure - A2A Marketplace: Deployment of decentralized trading for global energy and AI compute assets - Quantum Security: Implementation of post-quantum cryptography to secure large-scale industrial on-chain migration Dividends from this strategic investment will be dedicated to $PROS buybacks and will be shared with $PROS holders 🌊
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感谢@BlockFocus11 @byreal_io的圣诞礼盒,🍓很香甜,仪式感,圣诞氛围拉满了。 感恩遇见BF,期待2026年与BF的更多合作机会,可以解锁无限可能。 ㊗️BF的所有老师们 @CryptoErgou @MetaEu7 @Cryptowushi ¹²🎄₂₅ ≽^•༚• ྀི≼🎄 🧣- ̗̀圣诞快樂  ̖́-🐿️ 🎅🏻 ༘圣诞buff 好运叠满*.❅· 🍎「平安·喜樂 萬事·順意」▸ 𝐿𝑢𝑐𝑘𝑦
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Solana Breakpoint KOL afterparty ends with police intervention after crypto influencer caught having sex on roof of Abu Dhabi villa Police took guy to station, we all got away intact, not sure what punishment goes for public indecency in Abu Dhabi but praying for @cryptorapcalls
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@CryptoSnarko I seriously considered it, but I just finished this, no I need a breather: