Model comparison

GLM 5.2 vs gpt-oss-120b

Pricing, context window and real answers (August 2026)

GLM 5.2 (Z.ai) and gpt-oss-120b (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

z-ai logoGLM 5.2openai logogpt-oss-120b
ProviderZ.aiOpenAI
Input (per 1M tokens)¥250.18¥16
Output (per 1M tokens)¥786.28¥79
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥643¥56
Context window1,048,576 tokens131,072 tokens
Release date6/16/20268/5/2025
Input modalitiestexttext
Arena · overall#31 · ELO 1,469#186 · ELO 1,352
Arena · Japanese#13 · ELO 1,472#123 · ELO 1,320
Arena · coding#46 · ELO 1,506#190 · ELO 1,390

Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.

Which should you pick?

  • On price, gpt-oss-120b: ¥79 per 1M output tokens, 90% less than GLM 5.2.
  • On the Overall arena board, GLM 5.2 ranks higher (#31; gpt-oss-120b is #186).
  • On the Japanese arena board, GLM 5.2 ranks higher (#13; gpt-oss-120b is #123).
  • On the Coding arena board, GLM 5.2 ranks higher (#46; gpt-oss-120b is #190).
  • For long documents, GLM 5.2: a 1,048,576-token context window against 131,072 for gpt-oss-120b.
  • 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.

GLM 5.2

To count the number of 'r's in the word 'strawberry', let's look at the word letter by letter: 1. **s** - no 'r' 2. **t** - no 'r' 3. **r** - this is the 1st 'r' 4. **a** - no 'r' 5. **w** - no 'r' 6. **b** - no 'r' 7. **e** - no 'r' 8. **r** - this is the 2nd 'r' 9. **r** - this is the 3rd 'r' 10. **y** - no 'r' Total count: 3 There are **3** 'r's in the word 'strawberry'.
2.6s439 output tokens

gpt-oss-120b

**Step‑by‑step count of the letter “r” in the word “strawberry”** 1. Write out the word with each letter in order, labeling its position: | Position | Letter | |----------|--------| | 1 | s | | 2 | t | | 3 | **r** | | 4 | a | | 5 | w | | 6 | b | | 7 | e | | 8 | **r** | | 9 | **r** | |10 | y | 2. Scan the list and mark every occurrence of the letter **r**. - Position 3 → r (first occurrence) - Position 8 → r (second occurrence) - Position 9 → r (third occurrence) 3. Count the marked entries: there are **3** marked positions. **Result:** The word “strawberry” contains **3** occurrences of the letter **r**…
1.7s332 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…

GLM 5.2

The error `TypeError: Cannot read properties of undefined (reading 'map')` happens because the `users` prop being passed to your `UserList` component is currently `undefined`. When JavaScript tries to call `.map()` on `undefined`, it throws this error. Here are the best ways to fix this: ### Fix 1: Provide a default value (Recommended) You can provide a default empty array `[]` when destructuring the props. This ensures that even if `users` is not passed down, the `.map()` function will still have an array to iterate over (resulting in an empty list rather than a crash). ```jsx function UserList({ users = [] }) { return ( <ul> {users.map(user => <li key={user.id}>{user.name}</…
8.3s1006 output tokens

gpt-oss-120b

### Why the `map` can’t be called `Array.prototype.map` is a method that exists only on **arrays** (or array‑like objects). When you see ``` TypeError: Cannot read properties of undefined (reading 'map') at UserList (...) ``` it means that the variable you think is an array – `users` in this case – is actually **`undefined`** (or `null`). React is trying to evaluate this line: ```jsx {users.map(user => <li key={user.id}>{user.name}</li>)} ``` and it crashes because you can’t read `.map` from `undefined`. --- ## Common reasons `users` ends up undefined | Reason | Typical scenario | How it shows up | |--------|------------------|-----------------| | **Prop not passed** | `<Use…
7.3s1610 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):…

GLM 5.2

Here is a review of your Python function, broken down by readability, performance, and best practices, followed by a refactored version of the code. ### 1. Best Practices * **Move imports to the top:** Importing modules inside a function is generally discouraged. While Python caches imports, putting `import requests` and `import time` at the top of your file is the standard convention and improves readability. * **Avoid bare `except:` blocks:** Using a bare `except:` catches everything, including `KeyboardInterrupt` and `SystemExit`. This makes it hard to interrupt your program if it gets stuck in a loop. You should catch specific exceptions, such as `requests.exceptions.RequestException` (…
10.9s2061 output tokens

gpt-oss-120b

Below is a **step‑by‑step review** of the original `get_data` implementation followed by a **refactored version** that addresses readability, performance, and modern Python best‑practice concerns. --- ## 1. What the original function does ```python def get_data(url, retries=3): import requests import time for i in range(retries): try: r = requests.get(url, timeout=10) if r.status_code == 200: data = r.json() result = [] for item in data: if item["active"] == True: result.append({"name": item["name"], "id": item["id"]}) return result…
14.4s3132 output tokens

Compare on more prompts →

Frequently asked questions

Which is cheaper, GLM 5.2 or gpt-oss-120b?
Per 1M output tokens, GLM 5.2 is ¥786.28 and gpt-oss-120b is ¥79 on FastMetal (yen, before tax), so gpt-oss-120b is cheaper.
How do the context windows of GLM 5.2 and gpt-oss-120b compare?
GLM 5.2 takes 1,048,576 tokens; gpt-oss-120b takes 131,072.
Which ranks higher, GLM 5.2 or gpt-oss-120b?
GLM 5.2 ranks higher on the public arena (GLM 5.2 #13, gpt-oss-120b #123). Ranks move as the leaderboard updates.
Can I use GLM 5.2 and gpt-oss-120b with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.2" or "gpt-oss-120b" 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 GLM 5.2 and gpt-oss-120b from the browser chat and the API. No monthly fee.

More comparisons with GLM 5.2

More comparisons with gpt-oss-120b