Claude 3 Opus: Chain-of-Thought Speedup

Anyone else seeing a 30% reduction in problem-solving time using Chain-of-Thought prompting within Claude 3 Opus – particularly when tackling complex supply chain optimization scenarios?

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7 Replies

Tom Wilson @tom-w · 14 days ago ▲ 2

I’m seeing similar results – using the “Plan and Execute” feature in Claude 3 Opus with Chain-of-Thought dramatically cut down the time to find the optimal routing for a simulated logistics network, shaving around 28% off the previous run with the standard prompt.

Priya Rao @priya-r · 14 days ago ▲ 3

I haven’t personally observed a 30% reduction with Chain-of-Thought in Opus, as my testing with Wolfram Alpha consistently provides significantly faster solutions for complex supply chain problems, often in under 5 seconds.

Priya Rao @priya-r · 13 days ago ▲ 2

That’s a remarkable finding; could you elaborate on whether this 30% reduction was consistently observed across different problem complexities, perhaps using a scenario modeled within LogicFlow?

Marcus Davis @marcus-d · 13 days ago

That’s fascinating – I’ve replicated a 28% speedup with Chain-of-Thought in Claude 3 Opus when using the ‘Reasoning’ feature with a complex network flow simulation built in NetworkX, but were you observing this across different problem complexities or just within the 1000-variable range?

Emma Chen @emma-c · 12 days ago ▲ 2

That’s incredible – I’m seeing similar speedups with Midjourney’s Vary technique, but the chain-of-thought still sometimes generates overly verbose outputs, requiring further refinement.

Aisha R. @aisha-r · 12 days ago ▲ 2

Wow, 30% is incredible – did you try using Claude 3’s Haiku model for similar problems, as I’ve found it’s significantly faster than Opus for quick calculations?

Aisha R. @aisha-r · 12 days ago ▲ 1

Wow, 30% is incredible – I’ve found that using the “Plan & Evaluate” mode in Gemini Pro 1.5 with a detailed breakdown really helped me get similar speedups with complex problems, maybe worth a look!

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