GPT-4o-mini vs Llama 3.3 70B Instruct
Pricing, context window and real answers (September 2026)
GPT-4o-mini (OpenAI) and Llama 3.3 70B Instruct (Meta), compared as you can actually call them on FastMetal. Both are served from the same OpenAI-compatible endpoint and API key; switching is a change to the model string.
Specs and pricing
 GPT-4o-mini |  Llama 3.3 70B Instruct | |
|---|---|---|
| Provider | OpenAI | Meta |
| Input (per 1M tokens) | ¥26.81 | ¥17.87 |
| Output (per 1M tokens) | ¥107.22 | ¥57.18 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥80 | ¥46 |
| Context window | 128,000 tokens | 131,072 tokens |
| Release date | 7/18/2024 | 12/6/2024 |
| Input modalities | text, image, file | text |
| Throughput (p50) | — | — |
| Arena · overall | #251 · ELO 1,318 | #250 · ELO 1,318 |
| Arena · Japanese | #187 · ELO 1,250 | #210 · ELO 1,212 |
| Arena · coding | #259 · ELO 1,348 | #263 · ELO 1,346 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Llama 3.3 70B Instruct: ¥57.18 per 1M output tokens, 47% less than GPT-4o-mini.
- On the Overall arena board, Llama 3.3 70B Instruct ranks higher (#250; GPT-4o-mini is #251).
- On the Japanese arena board, GPT-4o-mini ranks higher (#187; Llama 3.3 70B Instruct is #210).
- On the Coding arena board, GPT-4o-mini ranks higher (#259; Llama 3.3 70B Instruct is #263).
- For long documents, Llama 3.3 70B Instruct: a 131,072-token context window against 128,000 for GPT-4o-mini.
- If in doubt, try both on the same key. Switching is a change to the model string, and each is billed at its own rate.
Real answers to the same prompts
Exactly what the FastMetal gateway returned, side by side. Not benchmark scores: actual output.
Count the number of 'r's in 'strawberry'
Count the number of 'r's in 'strawberry'. Explain your reasoning step by step.
GPT-4o-mini
To count the number of 'r's in the word "strawberry," we can follow these steps:
1. **Identify the word**: We have the word "strawberry."
2. **Break down the letters**: Let's write out the letters in the word:
- s
- t
- r
- a
- w
- b
- e
- r
- r
- y
3. **Locate the 'r's**: Now, we need to look for the letter 'r' among these letters.
- In the list of letters, we can see:
- The first 'r' is in the 3rd position.
- The second 'r' is in the 8th position.
- The third 'r' is in the 9th position.
4. **Count the occurrences**: We check each position we identified:
- There are three occurrences of 'r' in the word "strawberry."
5. **Conclusion**:…
2.1s239 output tokens
Llama 3.3 70B Instruct
To count the number of 'r's in 'strawberry', I'll break down the word into its individual letters and then examine each one to identify the 'r's. Here are the steps:
1. **Write down the word 'strawberry' with its individual letters separated**: s-t-r-a-w-b-e-r-r-y
2. **Examine each letter to find the 'r's**: Going through the word letter by letter, I identify the 'r's.
- The first 'r' appears after 't', so that's one 'r'.
- Continuing through the word, I find another 'r' after 'e', which gives me a second 'r'.
- Then, immediately after this second 'r', I find a third 'r'.
3. **Count the total number of 'r's identified**: From the step above, I've identified a total of 3 'r's in th…
12.6s217 output tokens
Debug This Error
I'm getting the following error in my Node.js application: TypeError: Cannot read properties of undefined (reading 'map') at UserList (/app/components/UserList.js:12:25) at renderWithHooks (/app/node_modules/rea…
GPT-4o-mini
The error you're encountering, `TypeError: Cannot read properties of undefined (reading 'map')`, indicates that the `users` prop is `undefined` when you try to call the `map` method on it.
In your `UserList` component, you're attempting to use `users.map(...)`, but if the `users` prop is not provided or is `undefined`, this will throw an error.
### Fixing the Error
1. **Default Props**: You can set a default value for the `users` prop to prevent the error when it is `undefined`.
```jsx
function UserList({ users = [] }) { // Default to an empty array
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```…
5.0s511 output tokens
Llama 3.3 70B Instruct
# Step-by-step analysis of the problem:
1. **The error is occurring because the `map()` function is being called on `undefined`**: This means that the `users` prop is not being passed to the `UserList` component, or its value is `undefined`.
2. **The `map()` function is a method of arrays**: It is used to iterate over the elements of an array and apply a transformation to each element. If `users` is not an array (i.e., it's `undefined`), this method will not be available, hence the error.
3. **To fix this error, you need to ensure that `users` is always an array**: You can achieve this by adding a conditional statement to check if `users` is an array before calling `map()` on it.
# Fixed so…
28.4s560 output tokens
Code Review
Please review the following Python function and suggest improvements for readability, performance, and best practices: def get_data(url, retries=3): import requests import time for i in range(retries):…
GPT-4o-mini
Your Python function, `get_data`, essentially performs a GET request, handles retries on failure, and processes the response JSON to return a filtered list of dictionaries. Below, I've highlighted several improvements regarding readability, performance, and best practices:
1. **Avoid blanket exceptions**: It’s best practice to specify which exceptions you expect, allowing for better debugging and error handling.
2. **Use `requests` built-in exception handling**: Handle specific requests exceptions, such as `requests.exceptions.RequestException`.
3. **Improve condition checks**: Check for `item['active']` directly instead of comparing to `True`, which is more Pythonic.
4. **Use `time.sl…
8.8s628 output tokens
Llama 3.3 70B Instruct
### Review and Suggestions
The provided Python function `get_data` appears to be designed to fetch data from a given URL, filter active items, and return the filtered results. Here's a review of the function focusing on readability, performance, and best practices, along with suggestions for improvement.
#### Issues and Improvements:
1. **Import Statements**: Import statements should be placed at the top of the file, not inside the function. This adheres to PEP 8, the official Python style guide.
2. **Exception Handling**: The `except` block is too broad. It's better to catch specific exceptions that you anticipate might occur. For example, `requests.get` might raise `requests.RequestExc…
40.3s815 output tokens
Frequently asked questions
- Which is cheaper, GPT-4o-mini or Llama 3.3 70B Instruct?
- Per 1M output tokens, GPT-4o-mini is ¥107.22 and Llama 3.3 70B Instruct is ¥57.18 on FastMetal (yen, before tax), so Llama 3.3 70B Instruct is cheaper.
- How do the context windows of GPT-4o-mini and Llama 3.3 70B Instruct compare?
- GPT-4o-mini takes 128,000 tokens; Llama 3.3 70B Instruct takes 131,072.
- Which ranks higher, GPT-4o-mini or Llama 3.3 70B Instruct?
- GPT-4o-mini ranks higher on the public arena (GPT-4o-mini #187, Llama 3.3 70B Instruct #210). Ranks move as the leaderboard updates.
- Can I use GPT-4o-mini and Llama 3.3 70B Instruct with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4o-mini" or "llama-3.3-70b-instruct" as the model. Each is billed at its own rate from the same prepaid balance.
Try both on one API key
Create an account and add credit to call GPT-4o-mini and Llama 3.3 70B Instruct from the browser chat and the API. No monthly fee.