Meta’s Watermelon model remains in active training as of early September 2026, following internal confirmation in July that it uses roughly ten times the compute of the Muse Spark series (codename Avocado) and matches GPT-5.5 on key benchmarks. Chief AI officer Alexandr Wang reiterated in early September that the project stays “on track” and will prove “very competitive,” yet no public release timeline or product integration details have been shared beyond internal targets pointing to October. Recent momentum instead centers on the September 3 rollout of Muse Spark 1.3, which narrows gaps in coding and agentic tasks but does not advance the larger Watermelon frontier effort. Traders price low near-term odds because frontier-model releases typically require completed safety reviews, API readiness, and public accessibility thresholds that have not yet been met, while October and November markets reflect the narrow window before year-end competitive pressure from OpenAI and Anthropic intensifies.
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
75%
$60 Vol.
September 30
14%
October 31
63%
November 30
75%
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 Watermelon model remains in active training as of early September 2026, following internal confirmation in July that it uses roughly ten times the compute of the Muse Spark series (codename Avocado) and matches GPT-5.5 on key benchmarks. Chief AI officer Alexandr Wang reiterated in early September that the project stays “on track” and will prove “very competitive,” yet no public release timeline or product integration details have been shared beyond internal targets pointing to October. Recent momentum instead centers on the September 3 rollout of Muse Spark 1.3, which narrows gaps in coding and agentic tasks but does not advance the larger Watermelon frontier effort. Traders price low near-term odds because frontier-model releases typically require completed safety reviews, API readiness, and public accessibility thresholds that have not yet been met, while October and November markets reflect the narrow window before year-end competitive pressure from OpenAI and Anthropic intensifies.
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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