Claude Haiku 5.5 vs Llama 3.1 8B Instruct
Pricing, context window and real answers (October 2026)
Claude Haiku 5.5 (Anthropic) 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
 Claude Haiku 5.5 |  Llama 3.1 8B Instruct | |
|---|---|---|
| Provider | Anthropic | Meta |
| Input (per 1M tokens) | $0.1055 | $0.0211 |
| Output (per 1M tokens) | $0.5275 | $0.0422 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $0.3693 | $0.0422 |
| Context window | 1,000,000 tokens | 131,072 tokens |
| Release date | 10/7/2026 | 7/23/2024 |
| Input modalities | text, image, file | text |
| Throughput (p50) | — | 36 tokens/s (n=18) |
| Arena · overall | Unranked | #340 · ELO 1,211 |
| Arena · Japanese | Unranked | #252 · ELO 1,087 |
| Arena · coding | Unranked | #334 · ELO 1,260 |
Prices are FastMetal's rates, before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-10-02; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- On price, Llama 3.1 8B Instruct: $0.0422 per 1M output tokens, 92% less than Claude Haiku 5.5.
- For long documents, Claude Haiku 5.5: a 1,000,000-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.
Claude Haiku 5.5
There are **3** r's in "strawberry."
1. **Spell out the word:** s, t, r, a, w, b, e, r, r, y
2. **Go through each letter and count the r's:**
- Position 3: **r** (count = 1)
- Position 8: **r** (count = 2)
- Position 9: **r** (count = 3)
3. **Check the rest:** s, t, a, w, b, e, and y are not r's.
Total: **3**
2.4s200 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…
Claude Haiku 5.5
The error means `users` is `undefined` when `UserList` renders, so `.map` is called on nothing. The component destructures the `users` prop, but the parent didn't pass it, or passed `undefined`.
## Common causes
**1. The parent doesn't pass the prop, or uses a different name**
```jsx
<UserList /> // users is undefined
<UserList user={users} /> // wrong name: "user" instead of "users"
```
**2. The data hasn't loaded yet (most common with fetched data)**
```jsx
function App() {
const [users, setUsers] = useState(); // undefined initially
useEffect(() => {
fetch('/api/users').then(r => r.json()).then(setUsers);
}, []);
return <UserList users={users} />;…
5.1s888 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):…
Claude Haiku 5.5
## Issues
**Correctness and robustness**
1. **Bare `except:`** catches everything, including `KeyboardInterrupt` and `SystemExit`, so Ctrl+C may not stop the program. Catch specific exceptions: `requests.RequestException` for network problems and `ValueError` for invalid JSON.
2. **Retries non-retryable errors.** A 404 or 401 won't succeed on retry, so retrying wastes time. Only retry transient failures such as 429, 5xx, timeouts, and connection errors.
3. **Sleeps after the final attempt.** The loop sleeps even when no retry follows.
4. **Fixed sleep with no backoff.** Exponential backoff is the standard approach for retries.
5. **Silent failure.** Every failure returns `[]` with no loggin…
18.1s4096 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, Claude Haiku 5.5 or Llama 3.1 8B Instruct?
- Per 1M output tokens, Claude Haiku 5.5 is $0.5275 and Llama 3.1 8B Instruct is $0.0422 on FastMetal (US dollars, before tax), so Llama 3.1 8B Instruct is cheaper.
- How do the context windows of Claude Haiku 5.5 and Llama 3.1 8B Instruct compare?
- Claude Haiku 5.5 takes 1,000,000 tokens; Llama 3.1 8B Instruct takes 131,072.
- Can I use Claude Haiku 5.5 and Llama 3.1 8B Instruct with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "anthropic-claude-haiku-5-5" 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 Claude Haiku 5.5 and Llama 3.1 8B Instruct from the browser chat and the API. No monthly fee.