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2127 points bakugo | 1 comments | | HN request time: 0.97s | source
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anotherpaulg ◴[] No.43164684[source]
Claude 3.7 Sonnet scored 60.4% on the aider polyglot leaderboard [0], WITHOUT USING THINKING.

Tied for 3rd place with o3-mini-high. Sonnet 3.7 has the highest non-thinking score, taking that title from Sonnet 3.5.

Aider 0.75.0 is out with support for 3.7 Sonnet [1].

Thinking support and thinking benchmark results coming soon.

[0] https://aider.chat/docs/leaderboards/

[1] https://aider.chat/HISTORY.html#aider-v0750

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anotherpaulg ◴[] No.43166754[source]
Using up to 32k thinking tokens, Sonnet 3.7 set SOTA with a 64.9% score.

  65% Sonnet 3.7, 32k thinking
  64% R1+Sonnet 3.5
  62% o1 high
  60% Sonnet 3.7, no thinking
  60% o3-mini high
  57% R1
  52% Sonnet 3.5
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pclmulqdq ◴[] No.43167134[source]
Also for $36.83 compared to o1's $186.50
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pzo ◴[] No.43168302[source]
But also for $36.83 compared to DeepSeek R1 + claude-3-5 it's $13.29 and for latter "Percent using correct edit format" is 100% vs 97.8% for 3.7.

edit: would be interesting to see how combo DeepSeek R1 + claude-3-7 performs.

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tw1984 ◴[] No.43168469[source]
is there any public info on why such DeepSeek R1 + claude-3-5 combo worked better than using a single model?
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WiSaGaN ◴[] No.43169721[source]
My personal experience is that R1 is smarter than 3.5 sonnet, but 3.5 sonnet is a better coder. Thus it may be better to let R1 to tackle the problem, but let 3.5 sonnet to implement the solution.
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1. pythonaut_16 ◴[] No.43171397[source]
Specialization of AI models is cool. Just like some people might be better planners and some are better at raw coding ability.