mayaskIn the ever-expanding realm of large language models (LLMs), two stand out prominently from the pack: Anthropic’s Claude 3.5 Sonnet and OpenAI’s GPT-4. Both these AIs boast remarkable capabilities, but which reigns supreme? This comprehensive guide delves deep into Claude 3.5 Sonnet and GPT-4, dissecting their strengths and weaknesses across various tasks.
Contents
- Pricing and tiers
- The Advantages of Using Claude
- The Advantages of Using GPT-4
- Speed and Accuracy Comparison
- Which One Is the Better Choice?
We’ll not only explore their relative accuracy and response speeds but also unpack their pricing structures and service tiers. By the end of this article, you’ll be armed with the knowledge to make a well-informed decision about which LLM best suits your specific needs and budget.
Recommended Videos
Pricing and tiers
ChatGPT users can access the GPT-4 model for free, but there are limitations on the number of queries allowed within a three-hour span. Exceeding that limit leads to using GPT-3.5, OpenAI’s older, less capable model, until the cooldown timer resets.
User’s who want to make full use of GPT-4 need to pay for the $20-per-month ChatGPT Plus subscription, a $30-per-month Teams subscription, or a market rate Enterprise sub. Paying for access not only increases the rate cap for using the AI model significantly but also grants access to additional features like Dall-E image generation.
Access to Claude is set up in a similar way. At the free tier, users can interact with the chatbot on the web or through the iOS app. They can also upload images and documents to the Anthropic server and query the AI about their contents, along with enjoying limited use of the new Claude 3.5 Sonnet model.
For a Pro account at $20 per month, users get everything from the free tier, along with higher usage limits, access to both Claude 3 Opus and Haiku, priority bandwidth and availability, and the ability to create Projects with the AI centered on a set of documents or files. A Teams account at $30 per month per person (minimum 5 people) offers even higher usage limits and the ability to share chats among teammates.
Advantages of using Claude
While Claude may not have the same widespread name recognition as GPT-4, Anthropic’s latest AI model has several advantages over its rival, not just in performance benchmarks. For one, Claude has a significantly larger context window than ChatGPT, allowing it to remember and analyze a much larger chunk of previous conversation or text, resulting in more nuanced and relevant responses, especially in longer interactions. Claude is also trained to prioritize accuracy over creativity in its responses.
It might struggle a bit in generating amusing haiku, but Claude excels at summarizing research papers and generating reports based on uploaded data. Additionally, Claude has a more recent knowledge cutoff date than GPT-4: April 2024 versus October 2023.
Moreover, Anthropic trained its Claude models as Constitutional AIs. This means the system implements a set of principles to make judgments about its generated outputs, effectively guiding the model towards the sort of ethical behavior dictated by the constitution. It includes avoiding toxic or discriminatory outputs and avoiding describing or advocating for illegal or unethical activities.
Advantages of using GPT-4
GPT-4 offers users a wider range of functions, a larger knowledge base, and more flexible log-in options compared to Claude.
Unlike Anthropic’s offering, ChatGPT can generate images (though that feature requires a subscription) and access the web to find the most up-to-date information available, not just the data it was trained on. And contrary to the sign-up process with Claude, GPT-4 users don’t have to provide their phone number for verification or any other credentials to start using the model. And thanks to its larger knowledge base, GPT-4 is more adept at generating creative content across images, text, and audio than Claude.
The ChatGPT website also tends to handle user requests with a much lower rate of overload compared to Claude.
Speed and accuracy comparison
Both models are capable of generating a wide variety of text outputs, from refining user-written prose to creating computer code and spreadsheet algorithms. When asked to generate a “piece of Python code that will measure the area of a circle and generate a graph of the function,” both models returned similarly structured snippets.
GPT-4 produced:
“`
import numpy as np
import matplotlib.pyplot as plt
# Function to calculate the area of a circle
def calculate_area(radius):
return np.pi * radius ** 2
# Generate a range of radius values
radii = np.linspace(0, 10, 100) # radii from 0 to 10 with 100 points
# Calculate the corresponding area values
areas = calculate_area(radii)
# Plotting the function
plt.figure(figsize=(10, 6))
plt.plot(radii, areas, label=’Area = πr²’)
plt.title(‘Area of a Circle as a Function of Radius’)
plt.xlabel(‘Radius’)
plt.ylabel(‘Area’)
plt.legend()
plt.grid(True)
plt.show()
“`
Claude’s response was a bit more detailed:
“`
import math
import numpy as np
import matplotlib.pyplot as plt
def circle_area(radius):
return math.pi * radius**2
# Generate radii from 0 to 10 with 100 points
radii = np.linspace(0, 10, 100)
# Calculate areas for each radius
areas = [circle_area(r) for r in radii]
# Create the plot
plt.figure(figsize=(10, 6))
plt.plot(radii, areas, ‘b-‘, linewidth=2)
plt.title(‘Area of a Circle as a Function of Radius’)
plt.xlabel(‘Radius’)
plt.ylabel(‘Area’)
plt.grid(True)
# Add some interesting points
plt.plot(0, circle_area(0), ‘ro’, label=’r = 0′)
plt.plot(1, circle_area(1), ‘ro’, label=’r = 1′)
plt.plot(5, circle_area(5), ‘ro’, label=’r = 5′)
plt.plot(10, circle_area(10), ‘ro’, label=’r = 10′)
plt.legend()
plt.show()
“`
In terms of image identification, the two models are closely matched. When asked to identify the various aspects of the following image, both GPT-4 and Claude 3.5 were able to easily find and describe each of the 21 items present.
When it comes to information about recent events, GPT-4 has the advantage as it can search the web for news that’s more recent than its training data. Asking Claude “what happened in Luxembourg yesterday” only gets a response saying: “I apologize, but I don’t have access to real-time news or information about specific events that occurred yesterday in Luxembourg. My knowledge cutoff is in April 2024, and I don’t have information about events after that date.” However, Claude does offer helpful recommendations on where to find the desired information.
I did find comparing the two systems to be a bit challenging, mainly because I was only able to make a half-dozen requests of Claude before it locked me out for three hours. Even on the free tier of ChatGPT, I won’t be completely locked out of the system; I’ll just have to interact with a slightly inferior model for a while.
Which is better?
Ultimately, the best choice depends on your specific needs. If you prioritize factual accuracy, long document processing, and have a tight budget, Claude might be a better fit. However, if you need a wider range of creative functionalities and are willing to pay for additional features, ChatGPT is still the preferred option.
In conclusion, both Claude 3.5 Sonnet and GPT-4 have their strengths and are suitable for different use cases. By understanding their advantages and considering your requirements, you can make a decision that aligns with your goals and preferences.
