Llama 3.1 8B Instruct vs Qwen3.8 2.4T A95B
Pricing, context window and real answers (September 2026)
Llama 3.1 8B Instruct (Meta) and Qwen3.8 2.4T A95B (Qwen), 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
 Llama 3.1 8B Instruct |  Qwen3.8 2.4T A95B | |
|---|---|---|
| Provider | Meta | Qwen |
| Input (per 1M tokens) | ¥8.94 | ¥351.83 |
| Output (per 1M tokens) | ¥14.3 | ¥1,055.5 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥16 | ¥880 |
| Context window | 131,072 tokens | 1,048,576 tokens |
| Release date | 7/23/2024 | 8/12/2026 |
| Input modalities | text | text |
| Throughput (p50) | — | — |
| Arena · overall | #329 · ELO 1,211 | Unranked |
| Arena · Japanese | #243 · ELO 1,087 | Unranked |
| Arena · coding | #323 · ELO 1,260 | Unranked |
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, 99% less than Qwen3.8 2.4T A95B.
- For long documents, Qwen3.8 2.4T A95B: 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.
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
Qwen3.8 2.4T A95B
To count the number of **“r”**s in **“strawberry”**, spell it out letter by letter:
**s t r a w b e r r y**
Now check each letter:
1. s — not r
2. t — not r
3. r — yes, count 1
4. a — not r
5. w — not r
6. b — not r
7. e — not r
8. r — yes, count 2
9. r — yes, count 3
10. y — not r
So there are **3** “r”s in **strawberry**.
1.3s203 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…
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
Qwen3.8 2.4T A95B
The error happens because `users` is `undefined` when React tries to render this line:
```js
{users.map(user => <li key={user.id}>{user.name}</li>)}
```
JavaScript cannot call `.map()` on `undefined`.
In your component:
```js
function UserList({ users }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
React expects `users` to be an array, but something is rendering `<UserList />` without providing a valid `users` prop.
---
## Common causes
### 1. The parent component is not passing `users`
For example:
```js
<UserList />
```
Instead of:
```js
<UserList users={users} />
```
---
### 2. The data has not loaded yet
If `users…
10.9s1318 output tokens
Professional Email
Write a professional email to a client explaining that the project delivery will be delayed by two weeks due to unexpected technical challenges discovered during integration testing. The tone should be apologetic but con…
Llama 3.1 8B Instruct
Subject: Project Update: Revised Timeline and Mitigation Steps
Dear [Client],
I am writing to inform you that, after careful review and analysis, our team has encountered unexpected technical challenges during integration testing that will require additional time to resolve. As a result, we are revising the project delivery timeline by two weeks.
I want to assure you that we are committed to delivering a high-quality solution that meets your expectations. Our team is working diligently to overcome these challenges and ensure a seamless delivery. The revised timeline is as follows:
**Original Timeline:** Project completion date: [Original Date]
**Revised Timeline:** Project completion dat…
19.2s342 output tokens
Qwen3.8 2.4T A95B
Subject: Updated Project Timeline – Revised Delivery Date
Dear [Client Name],
I hope this message finds you well.
I’m writing to provide an important update regarding the delivery timeline for [Project Name]. During our recent integration testing phase, we identified several unexpected technical challenges that require additional resolution to ensure the final deliverable meets the quality and performance standards we committed to.
After carefully reviewing the scope of these items with our technical team, we have determined that the project delivery will need to be extended by two weeks. I sincerely apologize for any inconvenience this may cause. Please be assured that we are taking imm…
4.6s449 output tokens
Frequently asked questions
- Which is cheaper, Llama 3.1 8B Instruct or Qwen3.8 2.4T A95B?
- Per 1M output tokens, Llama 3.1 8B Instruct is ¥14.3 and Qwen3.8 2.4T A95B is ¥1,055.5 on FastMetal (yen, before tax), so Llama 3.1 8B Instruct is cheaper.
- How do the context windows of Llama 3.1 8B Instruct and Qwen3.8 2.4T A95B compare?
- Llama 3.1 8B Instruct takes 131,072 tokens; Qwen3.8 2.4T A95B takes 1,048,576.
- Can I use Llama 3.1 8B Instruct and Qwen3.8 2.4T A95B with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "llama-3.1-8b-instruct" or "qwen3.8-2.4t-a95b" 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 Llama 3.1 8B Instruct and Qwen3.8 2.4T A95B from the browser chat and the API. No monthly fee.