Trader sentiment for the top AI model on LiveBench Mathematics by end of October shows closely matched odds near 50% for several leading developers, underscoring intense competition in mathematical reasoning benchmarks. No single lab holds a decisive edge, as performance hinges on factors like training data quality, chain-of-thought prompting refinements, and inference-time scaling rather than raw parameter counts. Recent model iterations from OpenAI, Anthropic, Google, and Chinese labs have narrowed gaps on math-specific tasks, with traders viewing outcomes as sensitive to any new releases, fine-tunes, or third-party evaluations before October. This uncertainty highlights how small capability gains can reorder leaderboards in fast-moving AI development.
Experimental AI-generated summary referencing Polymarket data. This is not trading advice and plays no role in how this market resolves. · UpdatedWhich company has the best AI model on LiveBench (Mathematics) end of October?
DeepSeek 59%
Tencent 56%
OpenAI 42%
Microsoft 35%

DeepSeek
59%

Tencent
56%

OpenAI
51%

Microsoft
35%

Z.ai
34%

Anthropic
18%

MiniMax
8%

Mistral
8%

ByteDance
5%

Alibaba
5%

Moonshot
5%

StepFun
5%

Amazon
4%

Thinky
4%

Baidu
4%

Nvidia
4%

Meta
2%

9%

Xiaomi
31%

SpaceXAI
33%

Meituan
-
DeepSeek 59%
Tencent 56%
OpenAI 42%
Microsoft 35%

DeepSeek
59%

Tencent
56%

OpenAI
51%

Microsoft
35%

Z.ai
34%

Anthropic
18%

MiniMax
8%

Mistral
8%

ByteDance
5%

Alibaba
5%

Moonshot
5%

StepFun
5%

Amazon
4%

Thinky
4%

Baidu
4%

Nvidia
4%

Meta
2%

9%

Xiaomi
31%

SpaceXAI
33%

Meituan
-
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.”
Market Opened: Aug 12, 2026, 8:04 PM ET
Resolver
0x69c47De9D...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.”
Resolver
0x69c47De9D...Trader sentiment for the top AI model on LiveBench Mathematics by end of October shows closely matched odds near 50% for several leading developers, underscoring intense competition in mathematical reasoning benchmarks. No single lab holds a decisive edge, as performance hinges on factors like training data quality, chain-of-thought prompting refinements, and inference-time scaling rather than raw parameter counts. Recent model iterations from OpenAI, Anthropic, Google, and Chinese labs have narrowed gaps on math-specific tasks, with traders viewing outcomes as sensitive to any new releases, fine-tunes, or third-party evaluations before October. This uncertainty highlights how small capability gains can reorder leaderboards in fast-moving AI development.
Experimental AI-generated summary referencing Polymarket data. This is not trading advice and plays no role in how this market resolves. · Updated
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