Model comparison

Llama 3.3 70B Instruct vs Muse Spark 1.2

Pricing, context window and real answers (September 2026)

Llama 3.3 70B Instruct (Meta) and Muse Spark 1.2 (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

meta-llama logoLlama 3.3 70B Instructmeta logoMuse Spark 1.2
ProviderMetaMeta
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 window131,072 tokens1,048,576 tokens
Release date12/6/20248/5/2026
Input modalitiestexttext, image, video, file, audio
Throughput (p50)
Arena · overall#250 · ELO 1,318#4 · ELO 1,500
Arena · Japanese#210 · ELO 1,212Unranked
Arena · coding#263 · ELO 1,346#9 · ELO 1,536

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 1.2.
  • On the Overall arena board, Muse Spark 1.2 ranks higher (#4; Llama 3.3 70B Instruct is #250).
  • On the Coding arena board, Muse Spark 1.2 ranks higher (#9; Llama 3.3 70B Instruct is #263).
  • For long documents, Muse Spark 1.2: 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 1.2

There are **3** 'r's in "strawberry". Here is my reasoning step by step: 1. Write out the word and its spelling: **s-t-r-a-w-b-e-r-r-y** 2. Go through each letter one by one and check if it is an 'r': * 1. s - not an 'r' -> count = 0 * 2. t - not an 'r' -> count = 0 * 3. **r** - yes, it's an 'r' -> count = 1 * 4. a - not an 'r' -> count = 1 * 5. w - not an 'r' -> count = 1 * 6. b - not an 'r' -> count = 1 * 7. e - not an 'r' -> count = 1 * 8. **r** - yes, it's an 'r' -> count = 2 * 9. **r** - yes, it's an 'r' -> count = 3 * 10. y - not an 'r' -> count = 3 3. Final total = **3**.
13.3s1123 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 1.2

This error means `users` is `undefined` when the component tries to render. You are calling `.map()` on `users` at line 12, but `.map()` only exists on arrays. If `users` is `undefined` or `null`, JavaScript throws: `Cannot read properties of undefined (reading 'map')`. This usually happens for 2 reasons: 1. You didn't pass the `users` prop to the component: `<UserList />` 2. Your data is async and `users` is `undefined` on the first render. For example: `const [users, setUsers] = useState()` without an initial value, and the data hasn't been fetched yet. ### Fix it You need to guarantee `users` is always an array before you call `.map()`. #### 1. Best Fix: Give it a default value U…
7.6s1142 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 1.2

Here is a review of your function with a refactored, production-ready version: ### Issues in the Current Version #### 1. Readability 1. **Generic name:** `get_data` tells nothing about what it does. `get_active_items` is better. 2. **Imports inside function:** `import requests, time` should be at the top of the file. It's slower and violates PEP 8. 3. **Magic numbers:** `200`, `10`, `2` have no context. 4. **Verbose loop:** Manual `for` loop + `append` can be replaced with a list comprehension. 5. **No documentation/typing:** No docstring, no type hints, so callers don't know what it expects or returns. 6. **`== True` is redundant:** `if item["active"] == True:` should be `if item["a…
11.8s2278 output tokens

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Frequently asked questions

Which is cheaper, Llama 3.3 70B Instruct or Muse Spark 1.2?
Per 1M output tokens, Llama 3.3 70B Instruct is ¥57.18 and Muse Spark 1.2 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 1.2 compare?
Llama 3.3 70B Instruct takes 131,072 tokens; Muse Spark 1.2 takes 1,048,576.
Which ranks higher, Llama 3.3 70B Instruct or Muse Spark 1.2?
Muse Spark 1.2 ranks higher on the public arena (Llama 3.3 70B Instruct #210, Muse Spark 1.2 #4). Ranks move as the leaderboard updates.
Can I use Llama 3.3 70B Instruct and Muse Spark 1.2 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "llama-3.3-70b-instruct" or "muse-spark-1.2" 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 1.2 from the browser chat and the API. No monthly fee.

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