Traders view the LiveBench Mathematics leaderboard at end of September 2026 as highly uncertain, with market-implied odds clustered near 50% across OpenAI, Anthropic, Google, Meta, DeepSeek, Moonshot and more than a dozen other labs. No single model holds a durable edge, reflecting rapid iteration cycles where gains in chain-of-thought reasoning, test-time compute scaling and specialized math fine-tuning can quickly reorder rankings on this contamination-resistant benchmark. Key swing factors include imminent model releases expected before September, developer conference announcements, and any new LiveBench problems that expose weaknesses in current frontier systems. Competitive dynamics hinge on which lab best combines scale, data quality and architectural innovations to push mathematical reasoning benchmarks higher in the coming weeks.
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OpenAI 50%
Anthropic 49%
Moonshot 48%
Nvidia 40%

OpenAI
50%

Anthropic
49%

Moonshot
48%

Nvidia
40%

Meta
23%

谷歌
23%

阿里巴巴
23%

Baidu
23%

MiniMax
23%

Mistral
23%

Meituan
23%

Z.ai
18%

Xiaomi
18%

SpaceXAI
18%

DeepSeek
18%

Amazon
18%

ByteDance
18%

Thinky
18%

腾讯
18%

StepFun
18%

微软
18%
OpenAI 50%
Anthropic 49%
Moonshot 48%
Nvidia 40%

OpenAI
50%

Anthropic
49%

Moonshot
48%

Nvidia
40%

Meta
23%

谷歌
23%

阿里巴巴
23%

Baidu
23%

MiniMax
23%

Mistral
23%

Meituan
23%

Z.ai
18%

Xiaomi
18%

SpaceXAI
18%

DeepSeek
18%

Amazon
18%

ByteDance
18%

Thinky
18%

腾讯
18%

StepFun
18%

微软
18%
Results from the “Mathematics” column of the leaderboard at https://livebench.ai/#/?cats=Mathematics, with the latest available LiveBench release selected and the category set to “Mathematics,” will be used to resolve this market.
Models will be ranked according to the specified score, with higher scores ranked ahead of lower scores. If two or more models have exactly the same score as displayed on the leaderboard, the model with the lower listed "cost per successful task" will be ranked ahead. 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 score and cost per successful task, “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 LiveBench leaderboard. 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 29, 2026, 6:14 PM ET
Results from the “Mathematics” column of the leaderboard at https://livebench.ai/#/?cats=Mathematics, with the latest available LiveBench release selected and the category set to “Mathematics,” will be used to resolve this market.
Models will be ranked according to the specified score, with higher scores ranked ahead of lower scores. If two or more models have exactly the same score as displayed on the leaderboard, the model with the lower listed "cost per successful task" will be ranked ahead. 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 score and cost per successful task, “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 LiveBench leaderboard. 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 LiveBench Mathematics leaderboard at end of September 2026 as highly uncertain, with market-implied odds clustered near 50% across OpenAI, Anthropic, Google, Meta, DeepSeek, Moonshot and more than a dozen other labs. No single model holds a durable edge, reflecting rapid iteration cycles where gains in chain-of-thought reasoning, test-time compute scaling and specialized math fine-tuning can quickly reorder rankings on this contamination-resistant benchmark. Key swing factors include imminent model releases expected before September, developer conference announcements, and any new LiveBench problems that expose weaknesses in current frontier systems. Competitive dynamics hinge on which lab best combines scale, data quality and architectural innovations to push mathematical reasoning benchmarks higher in the coming weeks.
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