In the rapidly expanding world of large language models (LLMs), two prominent contenders stand out: Anthropic’s Claude 3.5 Sonnet and OpenAI’s GPT-4o (the “o” stands for “Omni”). Both AIs boast impressive capabilities, but which one reigns supreme? This comprehensive guide delves into Claude 3.5 Sonnet and GPT-4o, dissecting their strengths and weaknesses across a range of tasks. We will explore their relative accuracy and response speeds, as well as their pricing structures and service tiers. By the end of this article, you will be equipped with the knowledge to make an informed decision about which LLM best suits your specific requirements and budget.
Pricing and Tiers
ChatGPT users can access the GPT-4o model for free, but the number of queries allowed within a three-hour window is limited. Exceeding this limit will switch you to GPT-3.5, OpenAI’s older and less capable model, until the cooldown timer resets. Users who want unlimited access to GPT-4o need to subscribe to the $20-per-month ChatGPT Plus, the $30-per-month Teams subscription, or an Enterprise subscription with a market rate. Paying for access not only dramatically increases the usage limit but also unlocks additional features like Dall-E image generation.
Access to Claude is structured similarly. The free tier allows users to 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, as well as enjoy limited use of the new Claude 3.5 Sonnet model. A $20-per-month Pro account offers all features of 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 AI-powered Projects centered on a set of documents or files. The Teams account, costing $30 per month per person (minimum 5 people), provides even higher usage limits and the capability to share chats between teammates.
Advantages of using Claude
While Claude might not enjoy the same level of recognition as GPT-4o, Anthropic’s latest AI model boasts a number of advantages over its rival, not just in performance benchmarks. One notable advantage is Claude’s significantly larger context window (200,000 characters versus 128,000). This allows Claude to remember and analyze a much larger chunk of previous conversation or text, resulting in more nuanced and relevant responses, especially in extended interactions.
Claude is also trained to prioritize accuracy over creativity in its responses. It might struggle with generating amusing haiku, but it excels at summarizing research papers and generating reports based on uploaded data. Claude’s knowledge cutoff date is also more recent than GPT-4o’s: April 2024 versus October 2023.
Furthermore, Anthropic trained its Claude models as Constitutional AIs. This means the system implements a set of principles to guide its generated outputs, effectively steering the model towards ethical behavior dictated by the constitution. This includes avoiding toxic or discriminatory outputs, as well as abstaining from describing or advocating for illegal or unethical activities.
Advantages of using GPT-4o
GPT-4o, on the other hand, offers users a wider range of functions, a larger knowledge base, and more flexible log-in options than Claude. Unlike Anthropic’s offering, ChatGPT can generate images (though this feature requires a subscription) and access the web to retrieve the most up-to-date information available, not just the data it was trained on. Unlike the sign-up process with Claude, GPT-4o users don’t need to provide their phone number for verification or any credentials at all to begin using the model.
Thanks to its larger knowledge base, GPT-4o is more adept at generating creative content across images, text, and audio than Claude. The ChatGPT website also tends to overload with user requests at a far lower rate than Claude’s.
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 tasked with generating 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-4o produced the following code:
python
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()
Meanwhile, Claude’s response was a bit more detailed:
python
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, both models perform similarly. When asked to identify various aspects of an image, both GPT-4o and Claude 3.5 were able to locate and describe each of the 21 items present.
GPT-4o has the advantage of delivering information about recent events, given its ability to search the web for news beyond its training data. Asking Claude “what happened in Luxembourg yesterday” only yields a response stating: “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.” The AI does offer helpful recommendations on where to find the requested information.
Comparing the two systems proved to be a challenge due to the three-hour lockout imposed on Claude after only a few requests. Even on the free tier of ChatGPT, I won’t be completely blocked from the system – I’ll simply have to converse with a slightly inferior model for a while.
Which is better?
The best LLM ultimately depends on your specific needs and priorities. Claude excels in accuracy and ethical behavior, while GPT-4o offers a wider range of features, including web access and image generation. Consider your usage requirements, budget, and preferred features to determine which LLM best aligns with your goals.
