Meta’s accelerated release cadence for the Muse Spark family of large language models drives current trader sentiment on the next 1.4+ version. Muse Spark 1.3 launched publicly on September 2 via Muse Code and the Meta Model API, delivering measurable gains in long-horizon agentic tasks and coding benchmarks such as DeepSWE while using roughly 20 percent fewer tool calls and 25 percent fewer tokens than 1.2. Chief AI Officer Alexandr Wang highlighted “frontier performance almost too cheap to meter” and referenced a larger codenamed “Watermelon” model plus upcoming open-weights releases. This follows 1.1 in July and 1.2 in early August, reflecting Meta Superintelligence Labs’ focus on competitive multimodal reasoning and developer API pricing against Anthropic and OpenAI. Key near-term catalysts include any confirmation of 1.4 timing or open-weight rollout before the October 31 resolution window.
基于Polymarket数据的AI实验性摘要。这不是交易建议,也不影响该市场的结算方式。 · 更新于9月30日
21%
10月31日
86%
$9,413 交易量
9月30日
21%
10月31日
86%
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.
市场开放时间: Sep 4, 2026, 10:28 AM ET
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.
Meta’s accelerated release cadence for the Muse Spark family of large language models drives current trader sentiment on the next 1.4+ version. Muse Spark 1.3 launched publicly on September 2 via Muse Code and the Meta Model API, delivering measurable gains in long-horizon agentic tasks and coding benchmarks such as DeepSWE while using roughly 20 percent fewer tool calls and 25 percent fewer tokens than 1.2. Chief AI Officer Alexandr Wang highlighted “frontier performance almost too cheap to meter” and referenced a larger codenamed “Watermelon” model plus upcoming open-weights releases. This follows 1.1 in July and 1.2 in early August, reflecting Meta Superintelligence Labs’ focus on competitive multimodal reasoning and developer API pricing against Anthropic and OpenAI. Key near-term catalysts include any confirmation of 1.4 timing or open-weight rollout before the October 31 resolution window.
基于Polymarket数据的AI实验性摘要。这不是交易建议,也不影响该市场的结算方式。 · 更新于



警惕外部链接哦。
警惕外部链接哦。
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