Inkling vs Muse Spark 1.3
Pricing, context window and real answers (September 2026)
Inkling (Thinking Machines) 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
| Inkling |  Muse Spark 1.3 | |
|---|---|---|
| Provider | Thinking Machines | 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 | 9/2/2026 |
| Input modalities | text, image, audio | text, image, video, file, audio |
| Arena · overall | #83 · ELO 1,439 | Unranked |
| Arena · Japanese | #54 · ELO 1,422 | Unranked |
| Arena · coding | #77 · ELO 1,491 | Unranked |
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 1.3.
- For long documents, Muse Spark 1.3: 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 1.3
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…
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 1.3
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):…
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 1.3
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, Inkling or Muse Spark 1.3?
- Per 1M output tokens, Inkling is ¥723.74 and Muse Spark 1.3 is ¥747.65 on FastMetal (yen, before tax), so Inkling is cheaper.
- How do the context windows of Inkling and Muse Spark 1.3 compare?
- Inkling takes 524,288 tokens; Muse Spark 1.3 takes 1,048,576.
- Can I use Inkling and Muse Spark 1.3 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "inkling" 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 Inkling and Muse Spark 1.3 from the browser chat and the API. No monthly fee.