Model comparison

GLM 5.1 vs GLM 5.3 FlashX

Pricing, context window and real answers (September 2026)

GLM 5.1 (Z.ai) and GLM 5.3 FlashX (Z.ai), 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 5.1z-ai logoGLM 5.3 FlashX
ProviderZ.aiZ.ai
Input (per 1M tokens)¥250.18¥66.12
Output (per 1M tokens)¥786.28¥223.38
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥643¥178
Context window204,800 tokens1,048,576 tokens
Release date4/7/20269/18/2026
Input modalitiestexttext, image, video
Throughput (p50)
Arena · overall#47 · ELO 1,466Unranked
Arena · Japanese#46 · ELO 1,434Unranked
Arena · coding#45 · ELO 1,513Unranked

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 FlashX: ¥223.38 per 1M output tokens, 72% less than GLM 5.1.
  • For long documents, GLM 5.3 FlashX: a 1,048,576-token context window against 204,800 for GLM 5.1.
  • 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 5.1

There are **3** 'r's in the word "strawberry". Here is the step-by-step reasoning: 1. Let's break down the word "strawberry" letter by letter: s - t - r - a - w - b - e - r - r - y 2. Now, let's check each letter one by one to see if it is an 'r': - **s**: not an 'r' - **t**: not an 'r' - **r**: this is the 1st 'r' - **a**: not an 'r' - **w**: not an 'r' - **b**: not an 'r' - **e**: not an 'r' - **r**: this is the 2nd 'r' - **r**: this is the 3rd 'r' - **y**: not an 'r' 3. Counting them up, there are three 'r's in total (in the 3rd, 8th, and 9th positions).
7.3s565 output tokens

GLM 5.3 FlashX

# Counting 'r's in "strawberry" **Step 1: Write out each letter with its position** | Position | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | |----------|---|---|---|---|---|---|---|---|---|----| | Letter | s | t | r | a | w | b | e | r | r | y | **Step 2: Check each letter one by one** - Position 1: **s** → not an 'r' - Position 2: **t** → not an 'r' - Position 3: **r** → ✅ 'r' found (count: 1) - Position 4: **a** → not an 'r' - Position 5: **w** → not an 'r' - Position 6: **b** → not an 'r' - Position 7: **e** → not an 'r' - Position 8: **r** → ✅ 'r' found (count: 2) - Position 9: **r** → ✅ 'r' found (count: 3) - Position 10: **y** → not an 'r' **Step 3: Tally the results** The 'r's a…
4.1s549 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 5.1

### What is causing the error? The error `TypeError: Cannot read properties of undefined (reading 'map')` means you are trying to call the `.map()` method on a variable that is `undefined`. In your code, the variable is `users`. When the `UserList` component renders, the `users` prop is `undefined`, so `undefined.map()` throws an error. ### Why is `users` undefined? This usually happens for one of two reasons: 1. **You forgot to pass the prop:** The parent component rendering `<UserList />` is not passing the `users` attribute (e.g., `<UserList />` instead of `<UserList users={myUsers} />`). 2. **Async Data Fetching:** You are fetching the users from an API. On the initial render, befor…
45.0s1680 output tokens

GLM 5.3 FlashX

## What's Happening The error means `users` is `undefined` at the time `UserList` renders. You're calling `.map()` on `undefined`, which JavaScript doesn't allow. This almost always happens for one of these reasons: 1. **The parent isn't passing the prop** — `<UserList />` with no `users` prop 2. **Data hasn't loaded yet** — you're fetching asynchronously, so the first render happens before the data arrives 3. **Prop name mismatch** — e.g., passing `user` but reading `users` 4. **Parent state initialized to `undefined`** — e.g., `useState()` instead of `useState([])` ## Fixes ### Option 1: Default parameter (simplest) ```jsx function UserList({ users = [] }) { return ( <ul>…
6.8s934 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 5.1

Here is a review of your function, broken down by areas for improvement, followed by a refactored version of the code. ### Key Areas for Improvement 1. **Imports Inside the Function:** Placing `import` statements inside a function is generally discouraged in Python. It slows down the function execution every time it is called, and it violates PEP 8 (the Python style guide). Imports should always be at the top of the module. 2. **Bare `except` Clause:** Using a bare `except:` catches *everything*, including `KeyboardInterrupt` and `SystemExit`, which makes it hard to terminate a hanging program. You should catch specific exceptions (like `requests.exceptions.RequestException`). 3. *…
70.3s2854 output tokens

GLM 5.3 FlashX

# Code Review The function works, but there are several issues worth addressing — including one subtle bug caused by the bare `except`. ## Correctness issues (most important) 1. **Bare `except:` is dangerous and masks a bug.** It catches *everything*, including `KeyboardInterrupt` and `SystemExit` (so Ctrl+C during a retry sleep is swallowed). Worse: because your data-processing loop sits inside the `try`, a `KeyError` from a malformed item is treated as a network failure — triggering a pointless re-download of the URL and silently discarding the real error. Catch only `requests.RequestException` (and `ValueError` for JSON decode failures). 2. **Silent failure.** Returning `[]` on error…
36.9s5836 output tokens

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Frequently asked questions

Which is cheaper, GLM 5.1 or GLM 5.3 FlashX?
Per 1M output tokens, GLM 5.1 is ¥786.28 and GLM 5.3 FlashX is ¥223.38 on FastMetal (yen, before tax), so GLM 5.3 FlashX is cheaper.
How do the context windows of GLM 5.1 and GLM 5.3 FlashX compare?
GLM 5.1 takes 204,800 tokens; GLM 5.3 FlashX takes 1,048,576.
Can I use GLM 5.1 and GLM 5.3 FlashX with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.1" or "glm-5.3-flashx" 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 5.1 and GLM 5.3 FlashX from the browser chat and the API. No monthly fee.

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