Of the three announcements Anthropic made on October 22, Claude 3.5 Haiku was the most interesting. Unlike the ‘new’ Claude 3.5 Sonnet, 3.5 Haiku is an actual successor to the Claude 3 Haiku – and now stands tall as the fastest and most efficient Anthropic model. But how well does it perform in coding tasks? And how well does it stack against OpenAI’s GPT-4o, 4o-mini, and Claude 3 Opus? (check new Claude 3.5 Sonnet vs. OpenAI o1 here)
This article will provide a detailed overview of Claude 3.5 Haiku and directly compare it with GPT 4o, 4o mini, and Claude 3 Opus. We’ll also share insights from social media for a broader perspective.
By the end, be rest assured you’ll know which model to use, where, and why.
Claude 3.5 Haiku Overview
Anthropic is positioning Claude 3.5 Haiku as the fastest and most cost-effective model within the Claude 3 family, which includes Claude 3 Opus and (new) Claude 3.5 Sonnet. It won’t be comparable to the 3.5 Sonnet, but is it any better than Opus? While Opus is recognized for its superior capabilities in complex tasks, Haiku excels in providing fast responses at a significantly lower cost—approximately one-tenth that of Opus at $0.25 per million input tokens and $1.25 per million output tokens. This cost-effectiveness makes Haiku a compelling choice for users who need affordability without sacrificing essential coding assistance features like generating snippets, debugging, and delivering clear explanations.
As for a ‘strengths and weaknesses’ analysis, results show that Claude 3.5 Haiku combines efficiency with clarity in its approach to programming assistance. The model produces concise code examples and clear explanations, which make it particularly valuable for developers aiming for quick solutions. Its strength in breaking down complex concepts and efficient debugging capabilities can benefit novice and experienced programmers alike. However, it has limitations in handling complex scenarios requiring deeper contextual understanding and isn’t as adaptable across different programming languages.
Claude 3.5 Haiku vs GPT-4o
Performance Comparison
- Speed: Claude 3.5 Haiku is designed for rapid responses, generating outputs at approximately 23 tokens per second. In contrast, GPT-4o excels with a much faster throughput of around 109 tokens per second, making it more suitable for real-time applications.
- Context Window: Claude 3.5 Haiku features a context window of 200,000 tokens, allowing it to handle extensive inputs effectively. GPT-4o has a smaller context window of 128,000 tokens, which may limit its ability to manage very long conversations or documents.
- Output Tokens: Claude 3.5 Haiku can generate up to 4,096 tokens in a single request, while GPT-4o supports up to 16,384 tokens. This larger output capacity in GPT-4o is advantageous for tasks requiring detailed responses.
Claude 3.5 Haiku vs GPT-4o Pricing
Claude 3.5 Haiku costs $0.25 for every million input tokens and $1.25 for every million output tokens. GPT-4o, on the other hand, is more expensive, costing $2.50 per million input tokens and $10 per million output tokens in standard mode. However, using the Batch API can reduce these costs to $1.25 and $5, respectively.
| Model | Input Cost (per million tokens) | Output Cost (per million tokens) |
| Claude 3.5 Haiku | $0.25 | $1.25 |
| GPT-4o | $2.50 (standard) / $1.25 (Batch API) | $10.00 (standard) / $5.00 (Batch API) |
Use Cases
- Coding Tasks: Claude 3.5 Haiku is particularly effective for coding-related tasks due to its clarity and debugging capabilities. It can quickly identify errors and suggest corrections.
- Creative Writing and Multimodal Tasks: GPT-4o shines in creative writing and multimodal tasks, handling text, images, audio, and video inputs effectively.
Try These Prompts
- Python: “Write a Python script that reads a text file and counts the number of times each word appears. Output the results in a dictionary format.”
- C: “Create a C program that takes an integer input from the user and checks if it’s a prime number. Print the result as either ‘Prime’ or ‘Not Prime.'”
Claude 3.5 Haiku vs GPT-4o Mini
Performance Comparison
- Speed: Claude 3.5 Haiku maintains its reputation for speed with quick output generation at around 23 tokens per second. GPT-4o Mini is also efficient but slightly slower than its larger counterpart.
- Context Window: Claude 3.5 Haiku supports a context window of 200,000 tokens, while GPT-4o Mini has a reduced context window of 128,000 tokens. This difference can impact performance in long-form content processing.
- Output Tokens: The maximum output for Claude 3.5 Haiku is limited to 4,096 tokens compared to GPT-4o Mini’s higher limit of 16,384 tokens.
Claude 3.5 Haiku vs GPT-4o Mini Pricing
Claude 3.5 Haiku is slightly more expensive than GPT-4o Mini, a more budget-friendly option, which costs $0.15 per million input tokens and $0.60 per million output tokens.
| Model | Input Cost (per million tokens) | Output Cost (per million tokens) |
| Claude 3.5 Haiku | $0.25 | $1.25 |
| GPT-4o Mini | $0.15 | $0.60 |
Use Cases
- Cost Efficiency: GPT-4o Mini is significantly cheaper than Claude 3.5 Haiku for both input and output costs, making it a better option for budget-conscious projects that still require quality performance.
- Real-Time Applications: Both models are suitable for real-time applications; however, the lower cost of GPT-4o Mini makes it more attractive for scenarios like customer support or high-frequency data processing.
Try These Prompts
- HTML: “Design a basic HTML page that includes a header, a paragraph of text, and an image. Use appropriate tags to ensure the content is structured correctly.”
- JavaScript: “Write a JavaScript function that takes an array of numbers and returns a new array containing only the even numbers from the original array.”
Claude 3.5 Haiku vs Claude 3 Opus
Performance Comparison
- Speed: Claude 3 Opus is slower than Claude 3.5 Haiku, generating outputs at about half the speed due to its focus on complex problem-solving capabilities.
- Context Window: Both models feature a context window of 200,000 tokens; however, Opus is designed to leverage this capacity for deeper understanding and more nuanced responses.
- Output Tokens: Like Haiku, Opus can generate up to 4,096 tokens in a single request but focuses on delivering high-quality outputs suitable for intricate tasks.
Claude 3.5 Haiku vs Claude 3 Opus Pricing
Claude 3.5 Haiku is significantly more affordable than Claude 3 Opus, which costs $15 per million input tokens and a hefty $75 per million output tokens.
| Model | Input Cost (per million tokens) | Output Cost (per million tokens) |
| Claude 3.5 Haiku | $0.25 | $1.25 |
| Claude 3 Opus | $15 (input MTok) | $75 (output MTok) |
Use Cases
- Complex Problem Solving: Claude 3 Opus is tailored for highly complex tasks that require advanced reasoning and multi-step logic, making it ideal for software development and intricate algorithm design.
- Collaboration Features: Opus includes features that facilitate teamwork among developers working on large-scale projects, which may not be as pronounced in the faster but simpler Haiku model.
Try These Prompts
- SQL: “Construct an SQL query to retrieve the names and email addresses of all users from a ‘users’ table where the user’s age is greater than 18.”
- HTML & JavaScript: “Create a simple web page using HTML and JavaScript that includes a button. When the button is clicked, display an alert with the message ‘Hello, World!'”
Detailed Comparative Analysis
To assist users in choosing the best model for their coding tasks, here’s a detailed comparative overview:
| Feature | Claude 3.5 Haiku | GPT-4o | GPT-4o Mini | Claude 3 Opus |
| Model Size | ~175 billion parameters | ~1 trillion parameters | ~175 billion parameters | ~175 billion parameters |
| Context Window | 200,000 tokens (500,000 tokens for enterprise) | 128,000 tokens | 128,000 tokens | 200,000 tokens |
| Conciseness | High | Moderate | High | Low |
| Clarity | High | High | Moderate | Moderate |
| Ideal Use Case | Quick solutions | Comprehensive tasks | Fast and accurate responses | Creative writing, complex analysis |
| Pricing (Estimated) | $0.25 per million input tokens$1.25 per million output tokens | $5 per million input tokens$15 per million output tokens | $0.15 per million input tokens$0.60 per million output tokens | $15 per million input tokens$75 per million output tokens |
Choosing the Right Model
When deciding between these models, consider the following factors:
- Task Complexity: For simple tasks or quick solutions, Claude 3.5 Haiku or GPT-4o Mini may suffice. For more complex problems requiring deep understanding and detailed explanations, opt for GPT-4o or Claude 3 Opus.
- Resource Availability: If you have limited computational resources or budget constraints, consider using Claude 3.5 Haiku or GPT-4o Mini as they are more accessible options compared to their larger counterparts.
- Learning vs. Development Needs: Beginners might benefit from the clarity of Claude 3.5 Haiku or the detailed explanations from GPT-4o. Experienced developers working on large projects may prefer the contextual awareness of GPT-4o or Claude 3 Opus due to their ability to integrate seamlessly into existing workflows.
The Bottom Line
It’s safe to say that Antropic’s recent announcement – while also met with hilarious criticism such as the screenshot below and Redditors unofficially calling the ‘new’ Claude 3.5 Sonnet ‘Claude 3.6’ or Claude 3.5.1 Sonnet – is quite notable.
While GPT 4o remains a close competitor, GPT-4o Mini strikes a balance between efficiency and simplicity but sacrifices some depth compared to its larger sibling. Claude 3 Opus excels in handling complex problems but demands more resources and may overwhelm beginners. Regardless, we hope you now know which model is best suited for what.
To try every model in the Claude 3 family, including the Claude 3.5 Sonnet, go to Bind AI Copilot. Let us know which model you prefer for your tasks on our Reddit community.