Claude Opus 4.8 vs GPT-5 Mini
Pricing, context window and real answers (September 2026)
Claude Opus 4.8 (Anthropic) and GPT-5 Mini (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
 Claude Opus 4.8 |  GPT-5 Mini | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Input (per 1M tokens) | ¥893.5 | ¥44.68 |
| Output (per 1M tokens) | ¥4,467.5 | ¥357.4 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥3,127 | ¥223 |
| Context window | 1,000,000 tokens | 400,000 tokens |
| Release date | 5/27/2026 | 8/7/2025 |
| Input modalities | text, image, file | text, image, file |
| Throughput (p50) | — | — |
| Arena · overall | #35 · ELO 1,473 | #163 · ELO 1,390 |
| Arena · Japanese | #27 · ELO 1,454 | #109 · ELO 1,365 |
| Arena · coding | #15 · ELO 1,530 | #172 · ELO 1,431 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GPT-5 Mini: ¥357.4 per 1M output tokens, 92% less than Claude Opus 4.8.
- On the Overall arena board, Claude Opus 4.8 ranks higher (#35; GPT-5 Mini is #163).
- On the Japanese arena board, Claude Opus 4.8 ranks higher (#27; GPT-5 Mini is #109).
- On the Coding arena board, Claude Opus 4.8 ranks higher (#15; GPT-5 Mini is #172).
- For long documents, Claude Opus 4.8: a 1,000,000-token context window against 400,000 for GPT-5 Mini.
- 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.
Claude Opus 4.8
# Counting 'r's in "strawberry"
## Step-by-step process:
Let me go through 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 |
## Answer:
There are **3** 'r's in "strawberry".
The three 'r's appear at positions 3, 8, and 9 — one after the "st" and two together in the "rry" ending.
4.5s262 output tokens
GPT-5 Mini
We examine the word "strawberry" letter by letter:
1. s — not an r (count = 0)
2. t — not an r (count = 0)
3. r — 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 — an r (count = 2)
9. r — an r (count = 3)
10. y — not an r (count = 3)
Total number of 'r's = 3.
5.2s382 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…
Claude Opus 4.8
# What's Causing the Error
The error tells you exactly what's happening:
```
TypeError: Cannot read properties of undefined (reading 'map')
at UserList (/app/components/UserList.js:12:25)
```
At the moment `UserList` renders, the `users` prop is `undefined`, and you can't call `.map()` on `undefined`. This is extremely common when data is fetched asynchronously—the component renders **before** the data arrives.
Common reasons `users` is undefined:
- The parent hasn't passed the `users` prop at all
- Data is still loading from an API (initial state is `undefined`)
- The API response shape differs from what you expect (e.g. `data.users` vs `data`)
---
# How to Fix It
## Option 1: De…
11.3s761 output tokens
GPT-5 Mini
That error means users is undefined when you call users.map(...). map is an Array method, so calling it on undefined throws "Cannot read properties of undefined (reading 'map')".
Common causes
- The parent component didn't pass a users prop.
- users is still loading (e.g. fetched asynchronously) and is null/undefined until the fetch completes.
- The parent initialized users to null instead of an empty array.
How to fix
Choose one or more of these approaches depending on your app:
1) Initialize the parent state as an array
If users is state in the parent, initialize it to [] so the child always receives an array:
const [users, setUsers] = useState([]);
// fetch and setUsers(data)
2) Give…
8.0s966 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):…
Claude Opus 4.8
# Code Review
Here's a breakdown of issues and suggested improvements for your function.
## Key Issues
1. **Imports inside the function** — should be at module level (runs on every call, harder to see dependencies).
2. **Bare `except:`** — catches everything, including `KeyboardInterrupt` and `SystemExit`. Silently swallowing errors makes debugging hard.
3. **Magic numbers** — `10`, `2`, `200` scattered around; extract as parameters/constants.
4. **`== True` comparison** — non-Pythonic; use the value directly (or `is True` if strict).
5. **Blocking `time.sleep(2)`** — fixed delay; exponential backoff is a better practice.
6. **`r.status_code == 200`** — misses other success codes; use `ra…
16.9s1403 output tokens
GPT-5 Mini
Thanks — this is a nice simple function, but it can be improved in several ways: move imports to module scope, avoid broad except:, use connection pooling (Session) for performance, use specific exception types, add logging and docstring, avoid comparing to True, use list comprehensions, validate JSON shape, and implement backoff (or use urllib3 Retry).
Below are two improved alternatives and a short rationale for the changes.
1) A simple, clear improvement (small changes, explicit errors, backoff + jitter)
- Moves imports to top-level
- Uses requests.Session for connection pooling
- Catches specific exceptions (requests.RequestException, ValueError)
- Uses list comprehension and item.get(…
13.6s1702 output tokens
Frequently asked questions
- Which is cheaper, Claude Opus 4.8 or GPT-5 Mini?
- Per 1M output tokens, Claude Opus 4.8 is ¥4,467.5 and GPT-5 Mini is ¥357.4 on FastMetal (yen, before tax), so GPT-5 Mini is cheaper.
- How do the context windows of Claude Opus 4.8 and GPT-5 Mini compare?
- Claude Opus 4.8 takes 1,000,000 tokens; GPT-5 Mini takes 400,000.
- Which ranks higher, Claude Opus 4.8 or GPT-5 Mini?
- Claude Opus 4.8 ranks higher on the public arena (Claude Opus 4.8 #27, GPT-5 Mini #109). Ranks move as the leaderboard updates.
- Can I use Claude Opus 4.8 and GPT-5 Mini with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "anthropic-claude-opus-4-8" or "gpt-5-mini" 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 Claude Opus 4.8 and GPT-5 Mini from the browser chat and the API. No monthly fee.