Ember-1 vs GPT-4.1 Nano
Pricing, context window and real answers (September 2026)
Ember-1 (Fireworks) and GPT-4.1 Nano (OpenAI), 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
| Ember-1 |  GPT-4.1 Nano | |
|---|---|---|
| Provider | Fireworks | OpenAI |
| Input (per 1M tokens) | ¥536.1 | ¥17.87 |
| Output (per 1M tokens) | ¥2,680.5 | ¥71.48 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥1,876 | ¥54 |
| Context window | 1,048,576 tokens | 1,047,576 tokens |
| Release date | 9/24/2026 | 4/14/2025 |
| Input modalities | text, image | image, text, file |
| Throughput (p50) | — | — |
| Arena · overall | Unranked | #243 · ELO 1,322 |
| Arena · Japanese | Unranked | #195 · ELO 1,234 |
| Arena · coding | Unranked | #226 · ELO 1,374 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GPT-4.1 Nano: ¥71.48 per 1M output tokens, 97% less than Ember-1.
- For long documents, Ember-1: a 1,048,576-token context window against 1,047,576 for GPT-4.1 Nano.
- 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.
Ember-1
# Counting the 'r's in "strawberry"
**Step 1: Write out the word letter by letter**
s - t - r - a - w - b - e - r - r - y
**Step 2: Examine each letter one at a time**
| Position | Letter | Is it 'r'? |
|----------|--------|------------|
| 1 | s | No |
| 2 | t | No |
| 3 | r | ✅ Yes (1) |
| 4 | a | No |
| 5 | w | No |
| 6 | b | No |
| 7 | e | No |
| 8 | r | ✅ Yes (2) |
| 9 | r | ✅ Yes (3) |
| 10 | y | No |
**Step 3: Verify by splitting the word into parts**
- "straw" → contains **1** r
- "berry" → contains **2** r's
- Total: 1 + 2 = **3**
## Answer
The word "strawberry" contains **3** r's.
8.2s482 output tokens
GPT-4.1 Nano
Let's analyze the word "strawberry" step by step to count the number of 'r's.
1. Write down the word: **strawberry**
2. Examine each letter one by one:
- s: no
- t: no
- r: yes (first 'r')
- a: no
- w: no
- b: no
- e: no
- r: yes (second 'r')
- r: yes (third 'r')
- y: no
3. Counting the 'r's found:
- First 'r' (at position 3)
- Second 'r' (at position 8)
- Third 'r' (at position 9)
So, there are **3** 'r's in "strawberry."
**Final answer: 3**
2.0s183 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…
Ember-1
## The Cause
The error means `users` is `undefined` when the component renders, so calling `.map()` on it fails. The component itself is fine — the problem is that the `users` prop isn't being provided (or isn't ready yet).
The most common reasons this happens:
1. **Async data hasn't loaded yet** — the parent fetches users from an API, and the component renders before the fetch completes:
```jsx
const [users, setUsers] = useState(); // undefined initially!
```
2. **The prop isn't passed or is misspelled** in the parent:
```jsx
<UserList user={users} /> // typo: should be "users"
```
3. **Wrong data shape** — e.g., passing the whole response object instead of `response…
18.2s960 output tokens
GPT-4.1 Nano
The error:
```
TypeError: Cannot read properties of undefined (reading 'map')
```
indicates that `users` is `undefined` at the time your `UserList` component is rendering, and you're trying to call `map` on it.
### Why is this happening?
In React, if a prop (`users` in this case) is not provided or is undefined, trying to do `users.map(...)` causes this error. This can happen if:
- The parent component does not pass `users`.
- `users` might be `null` or `undefined` initially, especially if data fetching is involved.
### How to fix it
**Option 1: Provide a default value for `users`**
Ensure that `users` defaults to an empty array if it is not provided:
```jsx
function UserList({ users…
4.3s514 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):…
Ember-1
# Code Review
## Bugs and correctness issues
- **Bare `except:`** catches *everything* — including `KeyboardInterrupt` and, critically, `KeyError` from `item["active"]`. A malformed item in the response would be misinterpreted as a network failure, wasting all your retries on a data problem that retrying can't fix.
- **Retrying all non-200 statuses** — a 404 or 401 will never succeed on retry. Only transient errors (connection failures, timeouts, 429, 5xx) are worth retrying.
- **Wasted sleep on the final attempt** — the loop sleeps 2 seconds even after the last failure, before returning `[]`.
- **Ambiguous return value** — `[]` means both "request failed" and "no active items." Callers ca…
95.0s5356 output tokens
GPT-4.1 Nano
Here's a review and an improved version of your function:
### Key improvements:
1. **Move imports to the top**: Imports should generally be at the top of the file, not inside functions.
2. **Specify exception types**: Catch specific exceptions rather than a generic `except`.
3. **Use context managers if needed**: Not necessary here, but good to consider.
4. **Avoid repeated code**: The sleep statement is the same whether there is a request exception or a non-200 status.
5. **Simplify filtering**: Use list comprehensions for clarity.
6. **Improve variable names**: For readability.
7. **Add optional headers or parameters** if needed (not required here).
8. **Optional:** Add more descriptive e…
3.4s391 output tokens
Frequently asked questions
- Which is cheaper, Ember-1 or GPT-4.1 Nano?
- Per 1M output tokens, Ember-1 is ¥2,680.5 and GPT-4.1 Nano is ¥71.48 on FastMetal (yen, before tax), so GPT-4.1 Nano is cheaper.
- How do the context windows of Ember-1 and GPT-4.1 Nano compare?
- Ember-1 takes 1,048,576 tokens; GPT-4.1 Nano takes 1,047,576.
- Can I use Ember-1 and GPT-4.1 Nano with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "ember-1" or "gpt-4.1-nano" 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 Ember-1 and GPT-4.1 Nano from the browser chat and the API. No monthly fee.