Inkling vs Muse Spark 1.2
Pricing, context window and real answers (August 2026)
Inkling (Thinkingmachines) 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
| Inkling |  Muse Spark 1.2 | |
|---|---|---|
| Provider | Thinkingmachines | Meta |
| Input (per 1M tokens) | ¥178.7 | ¥219.9 |
| Output (per 1M tokens) | ¥723.74 | ¥747.65 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥541 | ¥594 |
| Context window | 524,288 tokens | 1,048,576 tokens |
| Release date | 7/17/2026 | 8/5/2026 |
| Input modalities | text, image, audio | text, image, video, file, audio |
| Arena · overall | #81 · ELO 1,439 | #4 · ELO 1,498 |
| Arena · Japanese | #52 · ELO 1,425 | Unranked |
| Arena · coding | #80 · ELO 1,489 | #7 · ELO 1,533 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Inkling: ¥723.74 per 1M output tokens, 3% less than Muse Spark 1.2.
- On the Overall arena board, Muse Spark 1.2 ranks higher (#4; Inkling is #81).
- On the Coding arena board, Muse Spark 1.2 ranks higher (#7; Inkling is #80).
- For long documents, Muse Spark 1.2: a 1,048,576-token context window against 524,288 for Inkling.
- 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.
Inkling
Let's break down the word **"strawberry"** letter by letter:
1. **s**
2. **t**
3. **r** ← (1st 'r')
4. **a**
5. **w**
6. **b**
7. **e**
8. **r** ← (2nd 'r')
9. **r** ← (3rd 'r')
10. **y**
So the spelling is: s-t-**r**-a-w-b-e-**r**-**r**-y
Counting them up:
- One 'r' in "str" (the 3rd letter)
- Two 'r's in "berry" (the 8th and 9th letters)
**Total: 3 'r's** in "strawberry".**
2.4s417 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…
Inkling
The error occurs because `users` is `undefined` when `UserList` renders, so `users.map` fails.
This usually happens when:
- The parent doesn't pass the prop (`<UserList />` instead of `<UserList users={...} />`)
- Data is still loading (e.g., API hasn't returned yet)
## Quick Fix
Provide a default empty array so `.map` always has an array to work with:
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
Alternatively, guard against undefined explicitly:
```jsx
function UserList({ users }) {
if (!users) return null; // or a loading state
return (
<ul>
{users.map(user => <li key={…
4.9s585 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):…
Inkling
Here is a review with an improved version followed by explanations.
### Issues in the original
- **Imports inside the function**: Re-importing on every call is inefficient.
- **Bare `except:`**: Catches `SystemExit`, `KeyboardInterrupt`, etc.
- **Silent failures**: No logging; errors disappear.
- **Magic numbers**: `10`, `2`, `200` are hard-coded.
- **Data validation missing**: Assumes `data` is a list and every item has `"active"`, `"name"`, and `"id"` (will crash with `KeyError`).
- **Performance**: Uses `.append()` in a loop instead of a list comprehension.
- **Ambiguous return**: `[]` means both "success with no results" and "total failure".
### Improved version
```python
import loggi…
54.1s5649 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
Frequently asked questions
- Which is cheaper, Inkling or Muse Spark 1.2?
- Per 1M output tokens, Inkling is ¥723.74 and Muse Spark 1.2 is ¥747.65 on FastMetal (yen, before tax), so Inkling is cheaper.
- How do the context windows of Inkling and Muse Spark 1.2 compare?
- Inkling takes 524,288 tokens; Muse Spark 1.2 takes 1,048,576.
- Which ranks higher, Inkling or Muse Spark 1.2?
- Muse Spark 1.2 ranks higher on the public arena (Inkling #52, Muse Spark 1.2 #4). Ranks move as the leaderboard updates.
- Can I use Inkling and Muse Spark 1.2 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "inkling" 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 Inkling and Muse Spark 1.2 from the browser chat and the API. No monthly fee.