Will Anthropic have the best Math AI model at the end of May 2026?

Polymarket traders currently assign a 59.0% probability to "Will Anthropic have the best Math AI model at the end of May 2026?".

The market is pricing YES at 59.0¢ and NO at 40.0¢, reflecting current trader consensus.

Liquidity conditions are low, with approximately $1,146 in 24-hour trading activity.

Resolution Criteria

This market will resolve according to the company that owns the model that has the highest arena rank based on the Chatbot Arena LLM Leaderboard (https://lmarena.ai/) when the table under the "Leaderboard" tab for "Math" is checked on May 31, 2026, 12:00 PM ET.

Results from the "Rank" column under the "Text Arena | Math" Leaderboard tab at https://arena.ai/leaderboard/text/math-no-style-control 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 still 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 first place under this ranking.

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.

Market Interpretation

Prediction markets function as real-time consensus engines.

Traders continuously buy and sell outcome shares based on:

• breaking news
• macro developments
• public narratives
• institutional positioning
• probability reassessments

As a result, market pricing reflects aggregate trader expectations rather than static forecasts or polling systems.

At the current pricing structure:

• YES trades near 59.0¢
• NO trades near 40.0¢
• Implied probability sits near 59.0%

These probabilities may shift rapidly as new information enters the market.

Liquidity & Conviction Analysis

As of May 12, 2026 at 09:29 AM, liquidity conditions act as a primary structural filter on prediction market signal quality.

Medium liquidity conviction suggests moderate participation depth, where price discovery is active but not fully saturated by institutional or high-frequency flow.

Higher liquidity environments typically produce:

• tighter spreads
• faster price discovery
• stronger informational efficiency
• lower pricing instability

Lower liquidity environments tend to exhibit:

• wider spreads
• delayed consensus formation
• increased volatility from isolated trades
• weaker signal reliability in short time windows

Overall, liquidity acts as a direct proxy for how “stable” the implied probability surface is at any given moment.

Why This Signal Exists in Prediction Markets

Prediction markets function as continuous consensus engines where probability is not stated — it is priced.

Each trade updates a live belief distribution, turning scattered human judgment into a single evolving likelihood curve.

Compared to static polling or narrative reporting, this structure adapts instantly to:

• regime shifts in geopolitics
• macroeconomic shocks and policy changes
• institutional order flow and positioning
• narrative acceleration or decay
• liquidity-driven sentiment swings
• information asymmetry correction

In practice, these markets behave less like betting tools and more like real-time probabilistic sensors for world events.

They compress collective intelligence into a dynamic signal that updates with every transaction.

Market Structure Transition

As of May 12, 2026 at 09:29 AM, prediction markets have evolved into persistent global probability infrastructure.

Polymarket and Kalshi now operate as high-throughput probability engines, with cumulative volumes exceeding $150B+ and sustained monthly flow above $7B.

Market activity has shifted from episodic speculation toward continuous liquidity formation, where geopolitical events, macroeconomic narratives, elections, AI milestones, and financial expectations are constantly repriced in real time.

This transformation has turned prediction markets into always-on consensus surfaces capable of reflecting crowd intelligence faster than traditional media, polling systems, or institutional forecasting pipelines.