TOTAL VOLUME:
$134.1b
24H VOL:
$141,541,542
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,440,096,988
406,065
Markets across
30,522
events
MATCHED EVENTS:
2,692
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Jun 29, 8:00 PM EST
Polymarket
This market tracks which company will own the third-ranked AI model according to the Chatbot Arena LLM Leaderboard at the end of June 2026. On Polymarket, Anthropic holds a 79.5% probability of securing third place, while Google stands at 13.0%. The resolution will be determined by checking the Text Arena Overall Leaderboard rankings on June 30, 2026, at 12:00 PM ET, with ties broken by Arena score and then alphabetical order. Watch for major model releases and performance updates on the Chatbot Arena leaderboard leading up to the June 30, 2026 resolution checkpoint.
This market will resolve according to the company that owns the model that has the third-highest arena rank based on the Chatbot Arena LLM Leaderboard (https://lmarena.ai/) when the table under the "Leaderboard" tab is checked on June 30, 2026, 12:00 PM ET. Results from the "Rank" column under the "Text Arena | Overall" Leaderboard tab at https://lmarena.ai/leaderboard/text with style control off will be used to resolve this market. Models will be ordered primarily by their leaderboard rank at the market’s check time. If two or more models are tied on rank, they will be ordered by their Arena score, including any underlying, unrounded, granular values reflected in the data below the leaderboard. If a tie remains, alphabetical order of company names as listed in this market group will be used as a final tiebreaker (e.g., if the two models are tied by exact arena score, “Google” would be ranked ahead of “xAI”). This market will resolve based on the company that occupies third place under this ranking system. The resolution source for this market is the Chatbot Arena LLM Leaderboard found at https://lmarena.ai/. If this resolution source is unavailable at check time, this market will remain open until the leaderboard comes back online and will resolve based on the first check after it becomes available. If it becomes permanently unavailable, this market will resolve based on another resolution source.
Prediction market odds on Polymarket reflect real-time trader conviction and often diverge from traditional analyst forecasts. While analyst reports typically lag market sentiment and rely on published benchmarks, prediction markets incorporate forward-looking expectations and incorporate new AI capability announcements continuously. Traders pricing this event are betting on which company will rank third in model performance by Jun 30, 2026, a determination that depends on unreleased model evaluations and competitive developments. Market odds tend to react faster to emerging signals than formal analyst consensus, making them a complementary data source for tracking AI industry expectations.
The market resolves on Jun 30, 2026. Resolution hinges on identifying which company has the third best AI model as of that date. This determination will depend on publicly available model performance data, benchmark results, and credible third-party evaluations of AI capabilities at that time. The outcome reflects the ranking of AI models by performance metrics and real-world capability assessments available at resolution. Traders should monitor AI model releases, benchmark publications, and industry evaluations in the months leading up to the end date to assess how rankings may shift.
Key catalysts include major AI model releases and public benchmark results from leading companies. Announcements of new model versions, capability improvements, or performance breakthroughs could shift perceptions of which company ranks third. Academic papers, industry evaluations, and competitive comparisons published before Jun 30, 2026 will influence trader expectations. Regulatory developments affecting AI deployment, partnerships between AI companies, and acquisition activity could also reshape the competitive landscape. Real-world performance data from deployed models and user feedback will provide signals about relative model quality and capability rankings heading into resolution.