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Using 100 Claude Opus 5.5 agents reportedly did no better than using 10 on a problem

MTSlive quotes Planetary VC founder @ramez saying one agent's success was about 70%, rising three points with four.

Danielle Fong 🔆DF
MTSMT
2 Sources, 1h ago, first seen 1h ago

TLDR

MTSlive quotes Planetary VC founder @ramez discussing results from the Claude Opus 5.5 model card. He says one agent's success was about 70%, rising three points with four agents and another two points with 16. He says results topped out after 10 agents, with 100 doing no better, and argues that some problems depend more on one agent's ability than on a larger group.

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4K

2 Sources, first seen 1h ago

29 likes6 comments21 saves6 reposts

Combined views

4K

2 Sources, first seen 1h ago

29 likes6 comments21 saves6 reposts

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2 Sources

MTS@MTSlivePlanetary VC founder @ramez reveals that throwing 100 Claude Opus 5.5 agents at a problem was no better than using just 10, exposing a major limitation of AI swarms: "Test time compute scales worse than pre-training. Agents scale worse than test time compute. On the Opus 5.5 model card, it is like the worst scaling we've ever seen of anything." "The success of one agent was like 70%. It gained three points when you went to four agents, and then it gained two points when you went from four agents to 16. The Opus 5.5 model just topped out after 10 agents. It didn't get any better with 100 agents." "If you took the population of Columbus, Ohio, and said, 'Create general relativity,' would they do as well as Einstein on his own? There are many categories of problems where the peak intelligence of one entity is much more important than having a lot of entities at a lower level collaborating."1h
Danielle Fong 🔆@DanielleFongRT @MTSlive: Planetary VC founder @ramez reveals that throwing 100 Claude Opus 5.5 agents at a problem was no better than using just 10, ex…29m
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    2 Sources

    MTS@MTSlivePlanetary VC founder @ramez reveals that throwing 100 Claude Opus 5.5 agents at a problem was no better than using just 10, exposing a major limitation of AI swarms: "Test time compute scales worse than pre-training. Agents scale worse than test time compute. On the Opus 5.5 model card, it is like the worst scaling we've ever seen of anything." "The success of one agent was like 70%. It gained three points when you went to four agents, and then it gained two points when you went from four agents to 16. The Opus 5.5 model just topped out after 10 agents. It didn't get any better with 100 agents." "If you took the population of Columbus, Ohio, and said, 'Create general relativity,' would they do as well as Einstein on his own? There are many categories of problems where the peak intelligence of one entity is much more important than having a lot of entities at a lower level collaborating."1h
    Danielle Fong 🔆@DanielleFongRT @MTSlive: Planetary VC founder @ramez reveals that throwing 100 Claude Opus 5.5 agents at a problem was no better than using just 10, ex…29m
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