DeepSeek V4 Flash vs Llama 3.1 8B Instruct
Pricing, context window and real answers (September 2026)
DeepSeek V4 Flash (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 Flash |  Llama 3.1 8B Instruct | |
|---|---|---|
| Provider | DeepSeek | Meta |
| Input (per 1M tokens) | ¥24.61 | ¥8.94 |
| Output (per 1M tokens) | ¥49.21 | ¥14.3 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥49 | ¥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 | #92 · ELO 1,436 | #329 · ELO 1,211 |
| Arena · Japanese | #78 · ELO 1,396 | #243 · ELO 1,087 |
| Arena · coding | #92 · ELO 1,483 | #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, 71% less than DeepSeek V4 Flash.
- On the Overall arena board, DeepSeek V4 Flash ranks higher (#92; Llama 3.1 8B Instruct is #329).
- On the Japanese arena board, DeepSeek V4 Flash ranks higher (#78; Llama 3.1 8B Instruct is #243).
- On the Coding arena board, DeepSeek V4 Flash ranks higher (#92; Llama 3.1 8B Instruct is #323).
- For long documents, DeepSeek V4 Flash: 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 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
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 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
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 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
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 Flash or Llama 3.1 8B Instruct?
- Per 1M output tokens, DeepSeek V4 Flash is ¥49.21 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 Flash and Llama 3.1 8B Instruct compare?
- DeepSeek V4 Flash takes 1,048,576 tokens; Llama 3.1 8B Instruct takes 131,072.
- Which ranks higher, DeepSeek V4 Flash or Llama 3.1 8B Instruct?
- DeepSeek V4 Flash ranks higher on the public arena (DeepSeek V4 Flash #78, Llama 3.1 8B Instruct #243). Ranks move as the leaderboard updates.
- Can I use DeepSeek V4 Flash and Llama 3.1 8B Instruct with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4-flash" 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 Flash and Llama 3.1 8B Instruct from the browser chat and the API. No monthly fee.