DeepSeek V4 Flash vs GPT-4o-mini
Pricing, context window and real answers (September 2026)
DeepSeek V4 Flash (DeepSeek) and GPT-4o-mini (OpenAI), 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
 DeepSeek V4 Flash |  GPT-4o-mini | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Input (per 1M tokens) | ¥24.61 | ¥26.81 |
| Output (per 1M tokens) | ¥49.21 | ¥107.22 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥49 | ¥80 |
| Context window | 1,048,576 tokens | 128,000 tokens |
| Release date | 4/24/2026 | 7/18/2024 |
| Input modalities | text | text, image, file |
| Throughput (p50) | — | — |
| Arena · overall | #92 · ELO 1,436 | #251 · ELO 1,318 |
| Arena · Japanese | #78 · ELO 1,396 | #187 · ELO 1,250 |
| Arena · coding | #92 · ELO 1,483 | #259 · ELO 1,348 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, DeepSeek V4 Flash: ¥49.21 per 1M output tokens, 54% less than GPT-4o-mini.
- On the Overall arena board, DeepSeek V4 Flash ranks higher (#92; GPT-4o-mini is #251).
- On the Japanese arena board, DeepSeek V4 Flash ranks higher (#78; GPT-4o-mini is #187).
- On the Coding arena board, DeepSeek V4 Flash ranks higher (#92; GPT-4o-mini is #259).
- For long documents, DeepSeek V4 Flash: a 1,048,576-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.
DeepSeek V4 Flash
The word "strawberry" is spelled as s-t-r-a-w-b-e-r-r-y. I go through each letter: s (no), t (no), r (yes, first), a (no), w (no), b (no), e (no), r (yes, second), r (yes, third), y (no). Thus, there are three 'r's.
3.9s251 output tokens
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
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…
DeepSeek V4 Flash
The error occurs because `users` is `undefined` when the component tries to call `.map()` on it.
## Why this happens
Your component expects `users` to be an array, but it's receiving `undefined` as a prop. This typically happens when:
1. The parent component doesn't pass the `users` prop
2. The data fetching hasn't completed yet (async data loading)
3. The API response is missing the expected data structure
## How to fix it
### Option 1: Default prop value (Recommended for initial state)
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
### Option 2: Guard clause (More explicit)
```jsx
func…
6.3s422 output tokens
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
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):…
DeepSeek V4 Flash
Here's a comprehensive review with suggested improvements:
## Issues Identified:
1. **Import at wrong location** - Imports inside functions are inefficient and non-standard
2. **Bare `except:` clause** - Catches all exceptions including `KeyboardInterrupt`, `SystemExit`
3. **Missing error handling granularity** - Should distinguish between retryable and non-retryable errors
4. **Duplicate sleep logic** - Same sleep in `else` and `except` blocks
5. **Unnecessary variable** - `data` is only used once
6. **Inefficient list building** - Manual loop instead of list comprehension
7. **Hardcoded error message** - No logging or error context
8. **Missing type hints** - No type annotations
9. **Fun…
12.6s987 output tokens
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
Frequently asked questions
- Which is cheaper, DeepSeek V4 Flash or GPT-4o-mini?
- Per 1M output tokens, DeepSeek V4 Flash is ¥49.21 and GPT-4o-mini is ¥107.22 on FastMetal (yen, before tax), so DeepSeek V4 Flash is cheaper.
- How do the context windows of DeepSeek V4 Flash and GPT-4o-mini compare?
- DeepSeek V4 Flash takes 1,048,576 tokens; GPT-4o-mini takes 128,000.
- Which ranks higher, DeepSeek V4 Flash or GPT-4o-mini?
- DeepSeek V4 Flash ranks higher on the public arena (DeepSeek V4 Flash #78, GPT-4o-mini #187). Ranks move as the leaderboard updates.
- Can I use DeepSeek V4 Flash and GPT-4o-mini with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4-flash" or "gpt-4o-mini" 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 DeepSeek V4 Flash and GPT-4o-mini from the browser chat and the API. No monthly fee.