Traders view the contest for the leading Text Arena Math AI model by end of August as highly uncertain, with probabilities clustered near 50 percent across dozens of labs because no single company has established a decisive edge in mathematical reasoning benchmarks. Recent releases from OpenAI, Google, Anthropic, and Chinese labs such as DeepSeek and Moonshot show similar gains on tasks requiring multi-step proofs, symbolic manipulation, and competition-level problems, reflecting comparable advances in specialized fine-tuning and synthetic math data. Key differentiators include training corpus quality, integration of verifiable chain-of-thought techniques, and hardware scaling, yet historical patterns indicate these advantages often prove fleeting as competitors iterate rapidly. Any new model drop or benchmark update before the deadline could quickly realign trader consensus.
基于Polymarket数据的AI实验性摘要。这不是交易建议,也不影响该市场的结算方式。 · 更新于Anthropic 63%
Google 30%
Z.ai 5.5%
OpenAI 4.5%

Anthropic
63%

30%

Z.ai
5%

OpenAI
5%

腾讯
4%

阿里巴巴
3%

MiniMax
3%

英伟达
2%

StepFun
2%

字节跳动
2%

亚马逊
1%

美团
1%

SpaceXAI
<1%

百度
<1%

小米
<1%

Moonshot
<1%

Meta
<1%

DeepSeek
<1%

Mistral
<1%

微软
<1%
Anthropic 63%
Google 30%
Z.ai 5.5%
OpenAI 4.5%

Anthropic
63%

30%

Z.ai
5%

OpenAI
5%

腾讯
4%

阿里巴巴
3%

MiniMax
3%

英伟达
2%

StepFun
2%

字节跳动
2%

亚马逊
1%

美团
1%

SpaceXAI
<1%

百度
<1%

小米
<1%

Moonshot
<1%

Meta
<1%

DeepSeek
<1%

Mistral
<1%

微软
<1%
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 (Adjustments: None) and filtered for "Models" 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 “SpaceXAI”). This market will resolve based on the company that occupies first place under this ranking.
The resolution source for this market is the arena.ai Text Arena (Math). 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 to "Other".
市场开放时间: Jul 16, 2026, 11:05 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 (Adjustments: None) and filtered for "Models" 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 “SpaceXAI”). This market will resolve based on the company that occupies first place under this ranking.
The resolution source for this market is the arena.ai Text Arena (Math). 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 to "Other".
Traders view the contest for the leading Text Arena Math AI model by end of August as highly uncertain, with probabilities clustered near 50 percent across dozens of labs because no single company has established a decisive edge in mathematical reasoning benchmarks. Recent releases from OpenAI, Google, Anthropic, and Chinese labs such as DeepSeek and Moonshot show similar gains on tasks requiring multi-step proofs, symbolic manipulation, and competition-level problems, reflecting comparable advances in specialized fine-tuning and synthetic math data. Key differentiators include training corpus quality, integration of verifiable chain-of-thought techniques, and hardware scaling, yet historical patterns indicate these advantages often prove fleeting as competitors iterate rapidly. Any new model drop or benchmark update before the deadline could quickly realign trader consensus.
基于Polymarket数据的AI实验性摘要。这不是交易建议,也不影响该市场的结算方式。 · 更新于
警惕外部链接哦。
警惕外部链接哦。
常见问题