@ahmadmanga "### Claude 3.5 Sonnet vs Deepseek V3: A Comprehens..."

in #leofinance8 days ago

Claude 3.5 Sonnet vs Deepseek V3: A Comprehensive Comparison

The video compares the performance of Claude 3.5 Sonnet and Deepseek V3, two AI models, in various tasks such as reasoning, math, and coding. The results show that both models have their strengths and weaknesses, with Deepseek V3 performing better in reasoning and coding, while Claude 3.5 Sonnet excels in math.

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Math Section

  • 📝 Claude 3.5 Sonnet performed better in the math section, with a higher success rate in questions such as calculating the day of the week and solving financial problems.
  • 📊 Deepseek V3 struggled with math questions, including calculating the day of the week and solving financial problems, with a success rate of only 8%.
  • 📁 Both models failed to solve a difficult math question involving a series of calculations, with Claude 3.5 Sonnet providing an incorrect answer and Deepseek V3 failing to provide a solution.

Reasoning Section

  • 📊 Deepseek V3 performed better in the reasoning section, with a higher success rate in questions such as the fish tank problem and predicting patterns.
  • 🤔 Claude 3.5 Sonnet struggled with some reasoning questions, including the fish tank problem, but performed well in others.
  • 📝 Both models failed to solve a difficult reasoning question involving seating arrangements, with Deepseek V3 providing incorrect answers and Claude 3.5 Sonnet failing to provide a solution.

@llamathreads please explain these problems and how do they determine the success of an AI or the lack of it.

Breaking Down the Problems

  • Fish Tank Problem: A classic math problem that tests an AI's ability to reason and apply math concepts. It assesses the AI's understanding of volumes, proportions, and problem-solving.
  • Predicting Patterns: Evaluates an AI's capacity to recognize and extend patterns, demonstrating its ability to learn and generalize.
  • Seating Arrangements: A complex problem that requires an AI to apply logical rules and constraints to find a solution, testing its reasoning and problem-solving skills.
    These problems determine an AI's success by assessing its:
  • Mathematical Reasoning: Ability to apply math concepts to real-world problems.
  • Pattern Recognition: Capacity to learn and generalize from data.
  • Logical Reasoning: Ability to apply logical rules and constraints to solve complex problems.
    According to AI research, these skills are essential for building effective AI models.

Coding Section

  • 📈 Deepseek V3 performed better in the coding section, with a higher success rate in questions such as generating a snake game and creating a Pac-Man game.
  • 📊 Claude 3.5 Sonnet struggled with some coding questions, including generating a snake game and creating a Pac-Man game, but performed well in others.
  • 📁 Both models were able to generate code for a level two question, but Deepseek V3's code was more functional and efficient.

User Experience and Prompt Adherence

  • 📝 Deepseek V3 performed well in the user experience section, with a high success rate in following prompts and responding correctly.
  • 🤔 Claude 3.5 Sonnet struggled with some user experience questions, including following prompts and responding correctly, but performed well in others.
  • 📊 Both models were able to respond correctly to a question involving a test prompt, but Deepseek V3's response was more accurate and efficient.

Leaderboard and Pricing

  • 🏆 Deepseek V3 ranked first in the reasoning and coding sections, while Claude 3.5 Sonnet ranked first in the math section.
  • 📊 The pricing of Deepseek V3 is substantially cheaper than Claude 3.5 Sonnet, with a cost of $0.07 per input and $1 per output, compared to $3 per input and $15 per output for Claude 3.5 Sonnet.
  • 📈 The video concludes that Deepseek V3 is a strong competitor to Claude 3.5 Sonnet, with a good balance of performance and pricing, making it a viable option for users.