Meta's ongoing push to close the gap with OpenAI and Anthropic centers on Watermelon, its next frontier large language model after the Muse Spark series. Chief AI officer Alexandr Wang stated in July that the still-in-training model matches GPT-5.5 on internal benchmarks while using roughly 10 times the compute of prior versions. Internal documents from August targeted an October 2026 release, potentially powering consumer AI agents like the codenamed Hatch project. The September 3 launch of Muse Spark 1.3, with gains in coding and agentic capabilities, reinforces the timeline, though no public confirmation exists and product schedules often shift amid massive infrastructure spending. Traders watch for official announcements or benchmark leaks that could clarify resolution criteria.
Ringkasan eksperimental yang dihasilkan AI dengan referensi data Polymarket. Ini bukan saran trading dan tidak berperan dalam bagaimana pasar ini diselesaikan. · DiperbaruiSeptember 30
14%
October 31
63%
November 30
78%
$221 Vol.
September 30
14%
October 31
63%
November 30
78%
This market will resolve to "Yes" if Meta releases "Watermelon" or a model confirmed to be the model referenced above, and that model is made available to the general public by the listed date (ET). Otherwise, this market will resolve to "No".
A qualifying model must be named "Watermelon" or be identified, by Meta or by a consensus of credible reporting, as the model internally codenamed "Watermelon," regardless of the name under which it is ultimately released.
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.
Pasar Dibuka: Sep 4, 2026, 10:35 AM ET
Resolver
0x65070BE91...This market will resolve to "Yes" if Meta releases "Watermelon" or a model confirmed to be the model referenced above, and that model is made available to the general public by the listed date (ET). Otherwise, this market will resolve to "No".
A qualifying model must be named "Watermelon" or be identified, by Meta or by a consensus of credible reporting, as the model internally codenamed "Watermelon," regardless of the name under which it is ultimately released.
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.
Resolver
0x65070BE91...Meta's ongoing push to close the gap with OpenAI and Anthropic centers on Watermelon, its next frontier large language model after the Muse Spark series. Chief AI officer Alexandr Wang stated in July that the still-in-training model matches GPT-5.5 on internal benchmarks while using roughly 10 times the compute of prior versions. Internal documents from August targeted an October 2026 release, potentially powering consumer AI agents like the codenamed Hatch project. The September 3 launch of Muse Spark 1.3, with gains in coding and agentic capabilities, reinforces the timeline, though no public confirmation exists and product schedules often shift amid massive infrastructure spending. Traders watch for official announcements or benchmark leaks that could clarify resolution criteria.
Ringkasan eksperimental yang dihasilkan AI dengan referensi data Polymarket. Ini bukan saran trading dan tidak berperan dalam bagaimana pasar ini diselesaikan. · Diperbarui



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