How many more Millennium Prize Problems will AI solve in 2026?

According to the latest prediction market data for the query “How many more Millennium Prize Problems will AI solve in 2026?”, traders have formed a strong consensus.

Currently, 0 is dominating the market with an overwhelming 49.5% chance of winning. 1 follows in second place at 28.5%, while 2 sits in third with 14.5%. The betting volume for this specific market has already reached $78.4K, reflecting intense industry interest.

To better assess where each potential outcome stands, the market can be segmented into three distinct trading tiers based on implied probability and contract pricing:

🥇 Tier 1: The Dominant Leader

• 0 (49.5%): Currently commanding the highest probability, 0 is heavily favored by the order book. Traders looking to back this outcome face a “Buy Yes” contract price of 50¢, signaling a high degree of market conviction. This contract alone has generated $16.2K in volume.

🥈 Tier 2: The Primary Challengers

• 1 (28.5%): Positioned as the most viable alternative, 1 maintains a 28.5% chance of resolving true. Its “Buy Yes” shares currently trade at 28¢.
• 2 (14.5%): Sitting in third place with a 14.5% probability, the market shows measured skepticism toward 2, treating it as an outside wildcard unless momentum shifts.

🥉 Tier 3: The Long-Tail Options (Combining for ~7.5%)

Beyond the top three choices, a wide field of macro variables and long-shot outcomes are being tracked. While their individual probabilities hover low, they represent crucial hedges for speculative traders:

• Alternative Options: This includes 3 (6.8%), 4 (1.7%), and 5 (0.6%).
• Speculative Volume: Despite low statistical likelihood, certain long-tail contracts like 3 are still attracting notable interest.

This market will resolve according to the number of distinct qualifying Millennium Prize Problems for which an eligible AI lab announces a solution by December 31, 2026, 11:59 PM ET.

Each qualifying problem is counted once, regardless of how many eligible AI labs announce a solution to it or how many announcements are made.

The qualifying problems are, in alphabetical order, the Birch and Swinnerton-Dyer Conjecture, the Hodge Conjecture, P versus NP, the Riemann Hypothesis, and the Yang-Mills existence and mass gap problem (https://www.claymath.org/millennium-problems/). Announcements concerning the Navier-Stokes existence and smoothness problem will not qualify.

A qualifying announcement must be made by an eligible AI lab or an official representative of the lab, and must express that the problem has been solved; announcements of partial results or progress toward a solution will not qualify. The announcement must present the solution as the work of the lab, its researchers, or its models, alone or jointly with outside researchers. An announcement that only credits or congratulates outside researchers, including researchers who used the lab's models, compute, or research credits, will not qualify. No further confirmation from Clay Math Institute or any other organization is required.

The eligible AI labs are Anthropic, Google, SpaceXAI, Alibaba, OpenAI, Baidu, Z.ai, Xiaomi, Moonshot, Meta, Nvidia, DeepSeek, MiniMax, Meituan, Amazon, ByteDance, Mistral, Tencent, StepFun, Microsoft, Harmonic, Axiom Math, Math Inc, Safe Superintelligence, Thinking Machines Lab, Reflection AI, Periodic Labs, Apple, IBM, Huawei, Samsung, Oracle, Salesforce, Cohere, AI21 Labs, Reka, Sakana AI, Poolside, Magic, Perplexity, Anysphere, Kuaishou, SenseTime, iFlytek, Baichuan, and 01.AI, together with their subsidiaries and research divisions, and any other company with a model listed on the MMLU-pro leaderboard (https://huggingface.co/spaces/TIGER-Lab/MMLU-Pro) at the time of the announcement. Announcements by any other company, organization, or individual will not qualify.

The primary resolution source for this market will be official information from the eligible AI labs and/or their official representatives; however, a consensus of credible reporting may also be used.

While human consensus and speculative volume shape the broader prediction market, our quantitative algorithms offer a data-driven counter-perspective. By analyzing fundamental signals, underlying trends and historical distributions, our AI Valuation model calculates an independent “Fair Value” probability for each outcome.

Comparing this Fair Value against the current Trade Value uncovers major disparities — known as the Expected Value (EV) Gap. Contracts with a positive EV Gap represent statistically underpriced outcomes, whereas a negative EV Gap flags a potential market overreaction.

Top AI Alpha & Mispriced Arbitrage Opportunities

Based on the latest data model run, several key contracts stand out with significant deviations:

• The Most Overvalued Outcome 0 currently trades at 49.5%, but our AI places its Fair Value at just 34.4%. This creates a large negative EV Gap of -15.1%, suggesting the crowd may be overhyping this outcome and driving the premium too high.
• The Best Value Play (Highest EV) Our model identifies 1 as the premium value opportunity on the board. While the market only assigns it a 28.5% trading probability, our AI’s Fair Value assessment sits at 39.3% — yielding an impressive +10.8% EV Gap.
• Under-the-Radar Dark Horses Other notable discrepancies include 2 (EV Gap: +6.5%) and 3 (EV Gap: +0.6%). These long-tail opportunities are heavily discounted by the live order books despite stronger statistical backing from our predictive model.