DeepSeek V4 Pro vs Llama 3.1 8B Instruct
Pricing, context window and real answers (September 2026)
DeepSeek V4 Pro (DeepSeek) and Llama 3.1 8B 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
 DeepSeek V4 Pro |  Llama 3.1 8B Instruct | |
|---|---|---|
| Provider | DeepSeek | Meta |
| Input (per 1M tokens) | ¥341.32 | ¥8.94 |
| Output (per 1M tokens) | ¥684.42 | ¥14.3 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥684 | ¥16 |
| Context window | 1,048,576 tokens | 131,072 tokens |
| Release date | 4/24/2026 | 7/23/2024 |
| Input modalities | text | text |
| Throughput (p50) | — | — |
| Arena · overall | #57 · ELO 1,457 | #329 · ELO 1,211 |
| Arena · Japanese | #22 · ELO 1,462 | #243 · ELO 1,087 |
| Arena · coding | #65 · ELO 1,501 | #323 · ELO 1,260 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Llama 3.1 8B Instruct: ¥14.3 per 1M output tokens, 98% less than DeepSeek V4 Pro.
- On the Overall arena board, DeepSeek V4 Pro ranks higher (#57; Llama 3.1 8B Instruct is #329).
- On the Japanese arena board, DeepSeek V4 Pro ranks higher (#22; Llama 3.1 8B Instruct is #243).
- On the Coding arena board, DeepSeek V4 Pro ranks higher (#65; Llama 3.1 8B Instruct is #323).
- For long documents, DeepSeek V4 Pro: a 1,048,576-token context window against 131,072 for Llama 3.1 8B Instruct.
- 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 Pro
The word is "strawberry". Let's count the occurrences of the letter 'r' step by step:
1. Write the word: s t r a w b e r r y
2. Examine each character:
- s: not an 'r'
- t: not an 'r'
- r: is an 'r' → count 1
- a: not an 'r'
- w: not an 'r'
- b: not an 'r'
- e: not an 'r'
- r: is an 'r' → count 2
- r: is an 'r' → count 3
- y: not an 'r'
3. Total number of 'r's = 3.
Therefore, there are **3** 'r's in "strawberry".
7.3s1136 output tokens
Llama 3.1 8B Instruct
To count the number of 'r's in 'strawberry', I will break down the word into its individual letters and examine each one. Here's the step-by-step process:
1. The word 'strawberry' consists of the following letters: s-t-r-a-w-b-e-r-r-y.
2. I will start by counting the letters that are not 'r'. The word has 1 's', 1 't', 1 'a', 1 'w', 1 'b', 1 'e', 1 'y'.
3. Next, I will count the number of 'r's. The word has 2 'r's, one of which is part of the letter combination 'rr'.
Therefore, there are 2 'r's in the word 'strawberry'.
9.7s169 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 Pro
The error is occurring because `users` is `undefined` when the component renders, and you're trying to call `.map()` on it. This typically happens when the data hasn't been loaded yet or wasn't passed correctly to the component.
## Here are several ways to fix this:
### 1. **Add a default value with empty array (Simplest fix)**
```javascript
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
### 2. **Add a conditional check**
```javascript
function UserList({ users }) {
if (!users) {
return <div>No users found</div>;
}
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}<…
6.9s442 output tokens
Llama 3.1 8B Instruct
The error `TypeError: Cannot read properties of undefined (reading 'map')` typically occurs when you're trying to access a property (in this case, `map`) on an object that is `undefined`.
In your case, the `users` prop passed to the `UserList` component is `undefined`. This is likely because the parent component that renders `UserList` is not passing the `users` prop, or the prop is not being properly initialized.
To fix this error, you can add a simple check to ensure that `users` is not `undefined` before trying to call `map` on it:
```javascript
function UserList({ users }) {
if (!users) return null; // or return a default message, e.g. "No users found"
return (
<ul>
{us…
7.9s292 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 Pro
Here’s a review of your `get_data` function, highlighting issues and suggesting improvements.
## Overall Observations
- The function works but has several readability, robustness, and maintainability issues.
- Imports are inside the function, bare `except` hides errors, and the filtering logic is not Pythonic.
- No type hints or docstring, making it harder to use and understand.
## Specific Improvements
### 1. Move Imports to the Top of the Module
**Why:** Imports inside a function are executed every time the function is called, which is slightly slower and violates PEP 8 style guidelines.
**Before:**
```python
def get_data(url, retries=3):
import requests
import time
# ...
`…
40.5s2277 output tokens
Llama 3.1 8B Instruct
Here are some suggestions for improving the function's readability, performance, and best practices:
**Readability Improvements**
1. **Function name**: Consider renaming `get_data` to `fetch_active_items` to better reflect its purpose.
2. **Variable naming**: Use more descriptive variable names, such as `response` instead of `r`, and `active_items` instead of `result`.
3. **Code organization**: Break up the function into smaller, more focused sections. This will improve readability and make it easier to understand the logic.
4. **Type hints**: Add type hints for function parameters and return types to make the code more self-documenting.
**Performance Improvements**
1. **Use a more effic…
29.7s533 output tokens
Frequently asked questions
- Which is cheaper, DeepSeek V4 Pro or Llama 3.1 8B Instruct?
- Per 1M output tokens, DeepSeek V4 Pro is ¥684.42 and Llama 3.1 8B Instruct is ¥14.3 on FastMetal (yen, before tax), so Llama 3.1 8B Instruct is cheaper.
- How do the context windows of DeepSeek V4 Pro and Llama 3.1 8B Instruct compare?
- DeepSeek V4 Pro takes 1,048,576 tokens; Llama 3.1 8B Instruct takes 131,072.
- Which ranks higher, DeepSeek V4 Pro or Llama 3.1 8B Instruct?
- DeepSeek V4 Pro ranks higher on the public arena (DeepSeek V4 Pro #22, Llama 3.1 8B Instruct #243). Ranks move as the leaderboard updates.
- Can I use DeepSeek V4 Pro and Llama 3.1 8B Instruct with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4-pro" or "llama-3.1-8b-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 DeepSeek V4 Pro and Llama 3.1 8B Instruct from the browser chat and the API. No monthly fee.