Recent releases of frontier large language models have kept LiveBench coding scores tightly clustered, with Anthropic’s Claude Opus and Fable variants trading narrow leads against OpenAI’s GPT-5.x series and Google’s Gemini 3.5 updates in the latest refreshed tasks. Traders see comparable performance on agentic coding, multi-file refactoring, and execution accuracy, while Chinese labs such as Moonshot’s Kimi K3 and DeepSeek continue closing the gap on open-weight entries. The market’s flat 50 percent odds on multiple contenders reflect ongoing model refreshes, version-specific “high effort” modes, and the benchmark’s monthly question rotation that prevents any single lab from pulling decisively ahead before the August close.
Eksperymentalne podsumowanie AI odwołujące się do danych Polymarket. To nie jest porada handlowa i nie ma wpływu na rozstrzyganie tego rynku. · ZaktualizowanoWhich company has the best AI model on LiveBench (Coding) end of August?
Which company has the best AI model on LiveBench (Coding) end of August?
Anthropic 50%
Nvidia 50%
MiniMax 50%
OpenAI 49%
NOWE
NOWE
Aug 31, 2026
Anthropic
50%
Nvidia
50%
MiniMax
50%
OpenAI
49%
ByteDance
49%
Moonshot
49%
Alibaba
33%
Z.ai
33%
Xiaomi
33%
SpaceXAI
33%
Baidu
33%
DeepSeek
33%
Meta
33%
33%
Mistral
24%
Meituan
24%
Tencent
18%
StepFun
18%
Thinky
18%
Amazon
17%
Microsoft
17%
Anthropic 50%
Nvidia 50%
MiniMax 50%
OpenAI 49%
NOWE
NOWE
Aug 31, 2026
Anthropic
$0 Wol.
50%
Nvidia
$0 Wol.
50%
MiniMax
$0 Wol.
50%
OpenAI
$0 Wol.
49%
ByteDance
$0 Wol.
49%
Moonshot
$0 Wol.
49%
Alibaba
$0 Wol.
33%
Z.ai
$0 Wol.
33%
Xiaomi
$0 Wol.
33%
SpaceXAI
$0 Wol.
33%
Baidu
$0 Wol.
33%
DeepSeek
$0 Wol.
33%
Meta
$0 Wol.
33%
$0 Wol.
33%
Mistral
$0 Wol.
24%
Meituan
$0 Wol.
24%
Tencent
$0 Wol.
18%
StepFun
$0 Wol.
18%
Thinky
$0 Wol.
18%
Amazon
$0 Wol.
17%
Microsoft
$0 Wol.
17%
This market will resolve according to the company which owns the model with the highest Coding score on LiveBench.ai when the leaderboard is checked on August 31, 2026, at 12:00 PM ET.
Results from the “Coding” column of the leaderboard at https://livebench.ai/#/?cats=Coding, with the latest available LiveBench release selected and the category set to “Coding,” 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.”Recent releases of frontier large language models have kept LiveBench coding scores tightly clustered, with Anthropic’s Claude Opus and Fable variants trading narrow leads against OpenAI’s GPT-5.x series and Google’s Gemini 3.5 updates in the latest refreshed tasks. Traders see comparable performance on agentic coding, multi-file refactoring, and execution accuracy, while Chinese labs such as Moonshot’s Kimi K3 and DeepSeek continue closing the gap on open-weight entries. The market’s flat 50 percent odds on multiple contenders reflect ongoing model refreshes, version-specific “high effort” modes, and the benchmark’s monthly question rotation that prevents any single lab from pulling decisively ahead before the August close.
This market will resolve according to the company which owns the model with the highest Coding score on LiveBench.ai when the leaderboard is checked on August 31, 2026, at 12:00 PM ET.
Results from the “Coding” column of the leaderboard at https://livebench.ai/#/?cats=Coding, with the latest available LiveBench release selected and the category set to “Coding,” 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.”
Results from the “Coding” column of the leaderboard at https://livebench.ai/#/?cats=Coding, with the latest available LiveBench release selected and the category set to “Coding,” 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.”
Rynek otwarty: Jul 29, 2026, 6:27 PM ET
Wolumen
$0Data zakończenia
Aug 31, 2026Rynek otwarty
Jul 29, 2026, 6:27 PM ETŹródło rozstrzygnięcia
https://livebench.ai/#/?cats=CodingResolver
0x69c47De9D...This market will resolve according to the company which owns the model with the highest Coding score on LiveBench.ai when the leaderboard is checked on August 31, 2026, at 12:00 PM ET.
Results from the “Coding” column of the leaderboard at https://livebench.ai/#/?cats=Coding, with the latest available LiveBench release selected and the category set to “Coding,” 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.”Recent releases of frontier large language models have kept LiveBench coding scores tightly clustered, with Anthropic’s Claude Opus and Fable variants trading narrow leads against OpenAI’s GPT-5.x series and Google’s Gemini 3.5 updates in the latest refreshed tasks. Traders see comparable performance on agentic coding, multi-file refactoring, and execution accuracy, while Chinese labs such as Moonshot’s Kimi K3 and DeepSeek continue closing the gap on open-weight entries. The market’s flat 50 percent odds on multiple contenders reflect ongoing model refreshes, version-specific “high effort” modes, and the benchmark’s monthly question rotation that prevents any single lab from pulling decisively ahead before the August close.
This market will resolve according to the company which owns the model with the highest Coding score on LiveBench.ai when the leaderboard is checked on August 31, 2026, at 12:00 PM ET.
Results from the “Coding” column of the leaderboard at https://livebench.ai/#/?cats=Coding, with the latest available LiveBench release selected and the category set to “Coding,” 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.”
Results from the “Coding” column of the leaderboard at https://livebench.ai/#/?cats=Coding, with the latest available LiveBench release selected and the category set to “Coding,” 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.”
Wolumen
$0Data zakończenia
Aug 31, 2026Rynek otwarty
Jul 29, 2026, 6:27 PM ETŹródło rozstrzygnięcia
https://livebench.ai/#/?cats=CodingResolver
0x69c47De9D...Recent releases of frontier large language models have kept LiveBench coding scores tightly clustered, with Anthropic’s Claude Opus and Fable variants trading narrow leads against OpenAI’s GPT-5.x series and Google’s Gemini 3.5 updates in the latest refreshed tasks. Traders see comparable performance on agentic coding, multi-file refactoring, and execution accuracy, while Chinese labs such as Moonshot’s Kimi K3 and DeepSeek continue closing the gap on open-weight entries. The market’s flat 50 percent odds on multiple contenders reflect ongoing model refreshes, version-specific “high effort” modes, and the benchmark’s monthly question rotation that prevents any single lab from pulling decisively ahead before the August close.
Eksperymentalne podsumowanie AI odwołujące się do danych Polymarket. To nie jest porada handlowa i nie ma wpływu na rozstrzyganie tego rynku. · Zaktualizowano
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