Llama 3.3 70B Instruct vs Muse Spark 1.3
Pricing, context window and real answers (September 2026)
Llama 3.3 70B Instruct (Meta) and Muse Spark 1.3 (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
 Llama 3.3 70B Instruct | Muse Spark 1.3 | |
|---|---|---|
| Provider | Meta | Meta |
| Input (per 1M tokens) | ¥17.87 | ¥219.9 |
| Output (per 1M tokens) | ¥57.18 | ¥747.65 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥46 | ¥594 |
| Context window | 131,072 tokens | 1,048,576 tokens |
| Release date | 12/6/2024 | 9/2/2026 |
| Input modalities | text | text, image, video, file, audio |
| Throughput (p50) | — | — |
| Arena · overall | #250 · ELO 1,318 | #8 · ELO 1,493 |
| Arena · Japanese | #210 · ELO 1,212 | Unranked |
| Arena · coding | #263 · ELO 1,346 | #8 · ELO 1,537 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Llama 3.3 70B Instruct: ¥57.18 per 1M output tokens, 92% less than Muse Spark 1.3.
- On the Overall arena board, Muse Spark 1.3 ranks higher (#8; Llama 3.3 70B Instruct is #250).
- On the Coding arena board, Muse Spark 1.3 ranks higher (#8; Llama 3.3 70B Instruct is #263).
- For long documents, Muse Spark 1.3: a 1,048,576-token context window against 131,072 for Llama 3.3 70B 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 3.3 70B Instruct
To count the number of 'r's in 'strawberry', I'll break down the word into its individual letters and then examine each one to identify the 'r's. Here are the steps:
1. **Write down the word 'strawberry' with its individual letters separated**: s-t-r-a-w-b-e-r-r-y
2. **Examine each letter to find the 'r's**: Going through the word letter by letter, I identify the 'r's.
- The first 'r' appears after 't', so that's one 'r'.
- Continuing through the word, I find another 'r' after 'e', which gives me a second 'r'.
- Then, immediately after this second 'r', I find a third 'r'.
3. **Count the total number of 'r's identified**: From the step above, I've identified a total of 3 'r's in th…
12.6s217 output tokens
Muse Spark 1.3
The word is **strawberry** — there are **3** 'r's in it.
Here's my reasoning step by step:
1. **Write out the word:**
strawberry
2. **Break it into individual letters:**
s - t - r - a - w - b - e - r - r - y
3. **Go through each letter one by one and check if it is 'r':**
1. s → not r, count = 0
2. t → not r, count = 0
3. r → is r, count = 1
4. a → not r, count = 1
5. w → not r, count = 1
6. b → not r, count = 1
7. e → not r, count = 1
8. r → is r, count = 2
9. r → is r, count = 3
10. y → not r, count = 3
4. **Total up the matches:**
The 'r' appears at position 3, 8, and 9.
**Final answer: 3**
10.5s1063 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 3.3 70B Instruct
# Step-by-step analysis of the problem:
1. **The error is occurring because the `map()` function is being called on `undefined`**: This means that the `users` prop is not being passed to the `UserList` component, or its value is `undefined`.
2. **The `map()` function is a method of arrays**: It is used to iterate over the elements of an array and apply a transformation to each element. If `users` is not an array (i.e., it's `undefined`), this method will not be available, hence the error.
3. **To fix this error, you need to ensure that `users` is always an array**: You can achieve this by adding a conditional statement to check if `users` is an array before calling `map()` on it.
# Fixed so…
28.4s560 output tokens
Muse Spark 1.3
This error means `users` is `undefined` when your component tries to render.
`users.map(...)` only works if `users` is an array. On the first render, if you haven't passed the prop yet, or your data hasn't loaded from an API yet, `users` is `undefined`, so JavaScript throws:
> Cannot read properties of undefined (reading 'map')
This almost always happens in one of these 2 cases:
1. You forgot to pass the prop:
```js
<UserList /> // users is undefined!
```
vs.
```js
<UserList users={myUsers} />
```
2. Your data is async and is `undefined` on the first render:
```js
const [users, setUsers] = useState(); // undefined at first!
// ...
<UserList users={users} />
```
### How to fix it
**1.…
16.7s1242 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):…
Llama 3.3 70B Instruct
### Review and Suggestions
The provided Python function `get_data` appears to be designed to fetch data from a given URL, filter active items, and return the filtered results. Here's a review of the function focusing on readability, performance, and best practices, along with suggestions for improvement.
#### Issues and Improvements:
1. **Import Statements**: Import statements should be placed at the top of the file, not inside the function. This adheres to PEP 8, the official Python style guide.
2. **Exception Handling**: The `except` block is too broad. It's better to catch specific exceptions that you anticipate might occur. For example, `requests.get` might raise `requests.RequestExc…
40.3s815 output tokens
Muse Spark 1.3
Here's a friendly review of your `get_data` function — it works, but there are a few readability, robustness, and performance issues worth fixing:
### 1. Readability Issues
**a) Imports inside the function**
```python
import requests
import time
```
This runs on every call (though Python caches it). Move to the top of the file per PEP 8.
**b) Poor variable names & magic numbers**
`r`, `i`, `data`, `2`, `10`, `200` don't tell the reader much.
**c) `== True` anti-pattern**
```python
if item["active"] == True:
```
Just use `if item.get("active"):` or `is True`. The current version will also crash with `KeyError` if `active` is missing.
**d) No docstring / type hints**
No one knows what `ur…
26.9s2141 output tokens
Frequently asked questions
- Which is cheaper, Llama 3.3 70B Instruct or Muse Spark 1.3?
- Per 1M output tokens, Llama 3.3 70B Instruct is ¥57.18 and Muse Spark 1.3 is ¥747.65 on FastMetal (yen, before tax), so Llama 3.3 70B Instruct is cheaper.
- How do the context windows of Llama 3.3 70B Instruct and Muse Spark 1.3 compare?
- Llama 3.3 70B Instruct takes 131,072 tokens; Muse Spark 1.3 takes 1,048,576.
- Which ranks higher, Llama 3.3 70B Instruct or Muse Spark 1.3?
- Muse Spark 1.3 ranks higher on the public arena (Llama 3.3 70B Instruct #210, Muse Spark 1.3 #8). Ranks move as the leaderboard updates.
- Can I use Llama 3.3 70B Instruct and Muse Spark 1.3 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "llama-3.3-70b-instruct" or "muse-spark-1.3" 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 3.3 70B Instruct and Muse Spark 1.3 from the browser chat and the API. No monthly fee.