Model comparison

GLM 5.3 FlashX vs Muse Spark 1.3

Pricing, context window and real answers (September 2026)

GLM 5.3 FlashX (Z.ai) and Muse Spark 1.3 (Meta), 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 FlashXmeta logoMuse Spark 1.3
ProviderZ.aiMeta
Input (per 1M tokens)¥66.12¥219.9
Output (per 1M tokens)¥223.38¥747.65
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥178¥594
Context window1,048,576 tokens1,048,576 tokens
Release date9/18/20269/2/2026
Input modalitiestext, image, videotext, image, video, file, audio
Throughput (p50)
Arena · overallUnranked#8 · ELO 1,493
Arena · JapaneseUnrankedUnranked
Arena · codingUnranked#8 · ELO 1,537

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, 70% less than Muse Spark 1.3.
  • 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

Muse Spark 1.3

The word is **strawberry** — there are **3** 'r's in it. Here's my reasoning step by step: 1. **Write out the word:** strawberry 2. **Break it into individual letters:** s - t - r - a - w - b - e - r - r - y 3. **Go through each letter one by one and check if it is 'r':** 1. s → not r, count = 0 2. t → not r, count = 0 3. r → is r, count = 1 4. a → not r, count = 1 5. w → not r, count = 1 6. b → not r, count = 1 7. e → not r, count = 1 8. r → is r, count = 2 9. r → is r, count = 3 10. y → not r, count = 3 4. **Total up the matches:** The 'r' appears at position 3, 8, and 9. **Final answer: 3**
10.5s1063 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

Muse Spark 1.3

This error means `users` is `undefined` when your component tries to render. `users.map(...)` only works if `users` is an array. On the first render, if you haven't passed the prop yet, or your data hasn't loaded from an API yet, `users` is `undefined`, so JavaScript throws: > Cannot read properties of undefined (reading 'map') This almost always happens in one of these 2 cases: 1. You forgot to pass the prop: ```js <UserList /> // users is undefined! ``` vs. ```js <UserList users={myUsers} /> ``` 2. Your data is async and is `undefined` on the first render: ```js const [users, setUsers] = useState(); // undefined at first! // ... <UserList users={users} /> ``` ### How to fix it **1.…
16.7s1242 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

Muse Spark 1.3

Here's a friendly review of your `get_data` function — it works, but there are a few readability, robustness, and performance issues worth fixing: ### 1. Readability Issues **a) Imports inside the function** ```python import requests import time ``` This runs on every call (though Python caches it). Move to the top of the file per PEP 8. **b) Poor variable names & magic numbers** `r`, `i`, `data`, `2`, `10`, `200` don't tell the reader much. **c) `== True` anti-pattern** ```python if item["active"] == True: ``` Just use `if item.get("active"):` or `is True`. The current version will also crash with `KeyError` if `active` is missing. **d) No docstring / type hints** No one knows what `ur…
26.9s2141 output tokens

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Frequently asked questions

Which is cheaper, GLM 5.3 FlashX or Muse Spark 1.3?
Per 1M output tokens, GLM 5.3 FlashX is ¥223.38 and Muse Spark 1.3 is ¥747.65 on FastMetal (yen, before tax), so GLM 5.3 FlashX is cheaper.
How do the context windows of GLM 5.3 FlashX and Muse Spark 1.3 compare?
GLM 5.3 FlashX takes 1,048,576 tokens; Muse Spark 1.3 takes 1,048,576.
Can I use GLM 5.3 FlashX and Muse Spark 1.3 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.3-flashx" or "muse-spark-1.3" 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 Muse Spark 1.3 from the browser chat and the API. No monthly fee.

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