Next Muse Spark Model (1.4+) released on...?

根据「Next Muse Spark Model (1.4+) released on...?」的最新预测市场数据，交易者已形成强烈共识。

目前，No release by November 30 以压倒性的 64.5% 获胜概率主导市场；November 17 以 15% 位居第二，November 15 以 4.8% 排名第三。该市场的下注量已达 $40.2K，反映出市场的高度关注。

为了更好地评估各潜在结果的位置，可依据隐含概率与合约定价将市场划分为三个明显的交易梯队：

🥇 第一梯队：绝对领跑者

• No release by November 30 (64.5%)：No release by November 30 目前拥有最高概率，深受订单簿青睐。看好该结果的交易者面对的「Buy Yes」合约价为 65¢，显示出市场的高度确信。仅该合约就已产生 $25.2K 的成交量。

🥈 第二梯队：主要挑战者

• November 17 (15%)：作为最可行的替代选项，November 17 保持着 15% 的成真概率，其「Buy Yes」份额目前成交价为 15¢。
• November 15 (4.8%)：以 4.8% 的概率位列第三，市场对 November 15 持谨慎怀疑态度，除非势头转变，否则视其为外围黑马。

🥉 第三梯队：长尾选项（合计约 15.8%）

在前三名之外，还有大量宏观变量与冷门结果被持续追踪。尽管单个概率偏低，但它们是投机交易者的重要对冲：

• 替代选项：包括 November 28 (4.5%)、November 24 (3.9%)，以及 November 14 (3.7%)。
• 投机成交：尽管统计概率偏低，像 November 21 这类长尾合约仍吸引着可观的关注。

This market will resolve according to the calendar date (ET) on which Meta's next Muse Spark model (1.4+) is made available to the general public.

A qualifying model must have a name or model identifier that includes "Muse Spark" and be designated as version 1.4 or higher, regardless of capitalization, hyphenation, spacing, or surrounding prefixes, suffixes, dates, or descriptors. For example, a version 1.4 or higher named in the same manner as Muse Spark 1.2 or Muse Spark 1.3 would qualify, including a new whole-number generation such as Muse Spark 2, while models whose name does not include "Muse Spark" or which retain a version designation below 1.4, such as Muse Spark 1.3 (released September 2, 2026, including any of its reasoning modes, open-weight re-releases, rollouts, promotions, or snapshots), Muse Glimmer, or Muse Image, will not qualify.

A qualifying model must be launched and publicly accessible, including via open beta or open rolling waitlist signups. A closed beta or any form of private access will not suffice. The release must either be clearly defined and publicly announced by Meta as accessible to the general public, or otherwise be made publicly accessible and explicitly labeled on the company's official website. Labeling errors, placeholder text, or version names displayed on the website that do not correspond to a model that is actually accessible to the general public will not qualify.

The primary resolution source for this market will be official information from Meta, with additional verification from a consensus of credible reporting.

人群共识与投机成交塑造了更宏观的预测市场，而我们的量化算法提供了数据驱动的反向视角。通过分析基本面信号、底层趋势与历史分布，我们的 AI 估值模型为每个结果独立测算出一个「公允价值」概率。

将该公允价值与当前交易价值对比，可揭示出重大背离——即期望值（EV）差。正 EV 差代表统计上被低估的结果，而负 EV 差则提示市场可能存在反应过度。

顶级 AI Alpha 与错误定价套利机会

根据最新一轮数据模型测算，以下几个关键合约存在显著偏离：

• 最被高估的结果：November 17 当前交易价为 15%，但我们的 AI 测算其公允价值仅为 0.4%，形成 -14.6% 的较大负 EV 差，表明人群可能过度炒作该结果、把溢价推得过高。
• 最佳价值标的（最高 EV）：我们的模型将 November 18 识别为盘面上最具价值的机会。市场仅给予其 0.3% 的交易概率，而我们 AI 的公允价值评估为 1%——形成可观的 +0.8% EV 差。
• 被忽视的黑马：其他值得注意的偏离包括 November 27（EV 差：+0.6%）以及 November 26（EV 差：+0.6%）。尽管我们的预测模型给予更强的统计支撑，这些长尾机会仍被实时订单簿大幅低估。