Model comparison

GLM 5.3 FlashX vs Qwen3.8 27B

Pricing, context window and real answers (September 2026)

GLM 5.3 FlashX (Z.ai) and Qwen3.8 27B (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 5.3 FlashXqwen logoQwen3.8 27B
ProviderZ.aiQwen
Input (per 1M tokens)¥66.12¥80.41
Output (per 1M tokens)¥223.38¥571.84
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥178¥366
Context window1,048,576 tokens1,000,000 tokens
Release date9/18/20268/14/2026
Input modalitiestext, image, videotext, image, video
Throughput (p50)
Arena · overallUnranked#90 · ELO 1,437
Arena · JapaneseUnranked#91 · ELO 1,383
Arena · codingUnranked#67 · ELO 1,499

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, 61% less than Qwen3.8 27B.
  • For long documents, GLM 5.3 FlashX: a 1,048,576-token context window against 1,000,000 for Qwen3.8 27B.
  • 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 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

Qwen3.8 27B

The word is: **strawberry** Break it into letters: 1. s 2. t 3. r 4. a 5. w 6. b 7. e 8. r 9. r 10. y Now count the **r**’s: - 3rd letter: **r** - 8th letter: **r** - 9th letter: **r** So, there are **3** r’s in **strawberry**.
3.6s239 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 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

Qwen3.8 27B

The error means that `users` is `undefined` when `UserList` renders: ```jsx {users.map(...)} ``` JavaScript cannot call `.map()` on `undefined`. For example, this would cause the error: ```jsx <UserList /> ``` because `users` is not being passed in. ## Simple fix: give `users` a default value ```jsx function UserList({ users = [] }) { return ( <ul> {users.map(user => <li key={user.id}>{user.name}</li>)} </ul> ); } ``` Now if `users` is not passed in, it defaults to an empty array. ## Better fix: make sure the parent passes an array Wherever you use `UserList`, pass `users`: ```jsx <UserList users={users} /> ``` If `users` comes from an API or state, make sure it…
9.5s601 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 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

Qwen3.8 27B

The function works at a basic level, but it has several readability, reliability, and best-practice issues. ## Main issues 1. **Imports inside the function** ```python import requests import time ``` Imports should normally be at the top of the module unless there is a specific reason to lazy-load them. 2. **Bare `except` is too broad** ```python except: time.sleep(2) ``` This catches almost everything, including `KeyboardInterrupt`, `SystemExit`, `KeyError`, `TypeError`, and other programming errors. It makes debugging harder and can retry failures that should not be retried. 3. **It retries on every non-`200` status** Retrying `401 Unauthorized`, `4…
205.9s13103 output tokens

Compare on more prompts →

Frequently asked questions

Which is cheaper, GLM 5.3 FlashX or Qwen3.8 27B?
Per 1M output tokens, GLM 5.3 FlashX is ¥223.38 and Qwen3.8 27B is ¥571.84 on FastMetal (yen, before tax), so GLM 5.3 FlashX is cheaper.
How do the context windows of GLM 5.3 FlashX and Qwen3.8 27B compare?
GLM 5.3 FlashX takes 1,048,576 tokens; Qwen3.8 27B takes 1,000,000.
Can I use GLM 5.3 FlashX and Qwen3.8 27B with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.3-flashx" or "qwen3.8-27b" 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 FlashX and Qwen3.8 27B from the browser chat and the API. No monthly fee.

More comparisons with GLM 5.3 FlashX

More comparisons with Qwen3.8 27B