Model comparison

GLM 5.3 vs Qwen3.7 Max

Pricing, context window and real answers (August 2026)

GLM 5.3 (Z.ai) and Qwen3.7 Max (Qwen), 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 5.3qwen logoQwen3.7 Max
ProviderZ.aiQwen
Input (per 1M tokens)¥250.18¥263.58
Output (per 1M tokens)¥786.28¥790.75
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥643¥659
Context window1,048,576 tokens1,000,000 tokens
Release date8/18/20265/21/2026
Input modalitiestexttext
Arena · overallUnranked#21 · ELO 1,475
Arena · JapaneseUnrankedUnranked
Arena · codingUnranked#15 · ELO 1,526

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

Which should you pick?

  • On price, GLM 5.3: ¥786.28 per 1M output tokens, 1% less than Qwen3.7 Max.
  • For long documents, GLM 5.3: a 1,048,576-token context window against 1,000,000 for Qwen3.7 Max.
  • 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 5.3

# Counting 'r's in "strawberry" **Step 1: Spell out the word letter by letter.** s - t - r - a - w - b - e - r - r - y **Step 2: Go through each letter and mark the 'r's.** | Position | Letter | Is it 'r'? | |----------|--------|------------| | 1 | s | No | | 2 | t | No | | 3 | **r** | ✅ Yes (1st) | | 4 | a | No | | 5 | w | No | | 6 | b | No | | 7 | e | No | | 8 | **r** | ✅ Yes (2nd) | | 9 | **r** | ✅ Yes (3rd) | | 10 | y | No | **Step 3: Tally the results.** - 1st 'r' in "st**r**awberry" - 2nd 'r' in "strawbe**r**ry" - 3rd 'r' in "strawber**r**y" ## Answer: There are **3** 'r's in "strawberry." (Note: two of them appear together in the "rr" near the end, which is easy to miss when c…
5.8s493 output tokens

Qwen3.7 Max

To count the number of 'r's in the word "strawberry", let's break the word down letter by letter from left to right: 1. **s** - not an 'r' 2. **t** - not an 'r' 3. **r** - This is the **1st** 'r' 4. **a** - not an 'r' 5. **w** - not an 'r' 6. **b** - not an 'r' 7. **e** - not an 'r' 8. **r** - This is the **2nd** 'r' 9. **r** - This is the **3rd** 'r' 10. **y** - not an 'r' By examining each character individually, we can see that the letter 'r' appears in the 3rd, 8th, and 9th positions. Therefore, there are **3** 'r's in "strawberry".
15.1s842 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 5.3

## What's happening The error means `users` is `undefined` when the component renders. `undefined` doesn't have a `.map()` method, so JavaScript throws a `TypeError`. Since destructured props that aren't passed default to `undefined`, something upstream isn't providing the value you expect. ## Common causes 1. **The parent doesn't pass the prop, or uses a different name:** ```jsx <UserList /> {/* missing users */} <UserList userList={users} /> {/* prop name mismatch */} ``` 2. **Async data hasn't loaded yet** — the component renders before an API call completes, and the initial value is `undefined`: ```jsx const [users, setUsers] = useState(); // undefin…
17.1s1345 output tokens

Qwen3.7 Max

This error occurs because the `users` prop being passed to your `UserList` component is **`undefined`** at the time React tries to render it. JavaScript cannot call the `.map()` method on `undefined`, which throws the error. This usually happens for one of three reasons: 1. **Asynchronous Data Fetching:** The parent component is fetching `users` from an API. On the *initial render*, the data hasn't arrived yet, so the variable is `undefined`. 2. **Missing Prop:** The parent component forgot to pass the `users` prop (e.g., `<UserList />` instead of `<UserList users={myUsers} />`). 3. **Incorrect State Initialization:** The parent component initialized its state as `undefined` or `null` inste…
34.9s1851 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 5.3

Here's a breakdown of the issues, followed by a refactored version. ## Readability - **Move imports to module level.** PEP 8 requires top-level imports; importing inside a function hides dependencies and adds overhead on every call (small, but pointless). - **`item["active"] == True`** → just `item.get("active")`. Comparing to `True` with `==` is flagged by PEP 8, and `.get()` avoids a `KeyError` if the key is missing. - **Use a list comprehension** instead of initializing a list and appending in a loop. - **Rename things.** `get_data` doesn't say what it does (`fetch_active_items`?), and `response` beats `r`. Use `_` for the unused loop counter. - **Magic numbers** (`2`, `10`) should be n…
75.0s6434 output tokens

Qwen3.7 Max

Here is a comprehensive review of your function, broken down by readability, performance, and best practices, followed by a refactored version. ### 1. Readability & Style (PEP 8) * **Imports inside the function:** Imports should generally be placed at the top of the file, not inside the function. This makes dependencies clear and avoids slight overhead on every function call. * **`item["active"] == True`:** In Python, explicitly comparing to `True` is discouraged (PEP 8). You should just use `if item.get("active"):`. Using `.get()` also prevents `KeyError` if the key is missing. * **Manual List Building:** The `for` loop with `.append()` can be replaced with a much cleaner and faster **list…
58.3s3301 output tokens

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Frequently asked questions

Which is cheaper, GLM 5.3 or Qwen3.7 Max?
Per 1M output tokens, GLM 5.3 is ¥786.28 and Qwen3.7 Max is ¥790.75 on FastMetal (yen, before tax), so GLM 5.3 is cheaper.
How do the context windows of GLM 5.3 and Qwen3.7 Max compare?
GLM 5.3 takes 1,048,576 tokens; Qwen3.7 Max takes 1,000,000.
Can I use GLM 5.3 and Qwen3.7 Max with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.3" or "qwen3.7-max" 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 5.3 and Qwen3.7 Max from the browser chat and the API. No monthly fee.

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