GLM 5.3 FlashX vs MiMo-V2.5
Pricing, context window and real answers (September 2026)
GLM 5.3 FlashX (Z.ai) and MiMo-V2.5 (Xiaomi), 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
 GLM 5.3 FlashX | MiMo-V2.5 | |
|---|---|---|
| Provider | Z.ai | Xiaomi |
| Input (per 1M tokens) | ¥66.12 | ¥25.02 |
| Output (per 1M tokens) | ¥223.38 | ¥50.04 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥178 | ¥50 |
| Context window | 1,048,576 tokens | 1,050,000 tokens |
| Release date | 9/18/2026 | 4/22/2026 |
| Input modalities | text, image, video | text, audio, image, video |
| Throughput (p50) | — | — |
| Arena · overall | Unranked | #96 · ELO 1,434 |
| Arena · Japanese | Unranked | #141 · ELO 1,321 |
| Arena · coding | Unranked | #81 · ELO 1,491 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, MiMo-V2.5: ¥50.04 per 1M output tokens, 78% less than GLM 5.3 FlashX.
- For long documents, MiMo-V2.5: a 1,050,000-token context window against 1,048,576 for GLM 5.3 FlashX.
- 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
MiMo-V2.5
# Counting the 'r's in 'strawberry'
Let me spell the word out letter by letter:
| Position | Letter | Is it 'r'? |
|----------|--------|------------|
| 1 | **s** | ❌ |
| 2 | **t** | ❌ |
| 3 | **r** | ✅ (1) |
| 4 | **a** | ❌ |
| 5 | **w** | ❌ |
| 6 | **b** | ❌ |
| 7 | **e** | ❌ |
| 8 | **r** | ✅ (2) |
| 9 | **r** | ✅ (3) |
| 10 | **y** | ❌ |
## Answer: **3** 'r's
The three r's are found at positions **3**, **8**, and **9** in the word.
14.9s313 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
MiMo-V2.5
This error occurs because your `users` prop is `undefined` when the component tries to call `.map()` on it. This usually happens when:
1. The parent component doesn't pass a `users` prop
2. The `users` data is still loading (asynchronous operation)
3. There's a typo in the prop name when passing from parent
## How to Fix It
### 1. Add Default Props or Prop Validation
Add a default value for the `users` prop:
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
// Or with PropTypes
import PropTypes from 'prop-types';
function UserList({ users }) {
return (
<ul>
{users.map(user => <li key…
11.2s808 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
MiMo-V2.5
# Code Review: `get_data` Function
## Issues Identified
| Category | Issue | Severity |
|----------|-------|----------|
| Style | Imports inside function body | Medium |
| Reliability | Bare `except` catches `KeyboardInterrupt`/`SystemExit` | High |
| Reliability | Silent failures — no logging | Medium |
| Readability | `== True` comparison (redundant) | Low |
| Readability | No docstring or type hints | Medium |
| Performance | Could use list comprehension | Low |
| Robustness | No exponential backoff on retries | Medium |
| Robustness | `r.json()` can fail silently under bare except | High |
| Style | Uninformative variable names (`r`, `i`) | Low |
| Config | Magic numbers hardcoded (`ti…
33.6s1854 output tokens
Frequently asked questions
- Which is cheaper, GLM 5.3 FlashX or MiMo-V2.5?
- Per 1M output tokens, GLM 5.3 FlashX is ¥223.38 and MiMo-V2.5 is ¥50.04 on FastMetal (yen, before tax), so MiMo-V2.5 is cheaper.
- How do the context windows of GLM 5.3 FlashX and MiMo-V2.5 compare?
- GLM 5.3 FlashX takes 1,048,576 tokens; MiMo-V2.5 takes 1,050,000.
- Can I use GLM 5.3 FlashX and MiMo-V2.5 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.3-flashx" or "mimo-v2.5" 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 MiMo-V2.5 from the browser chat and the API. No monthly fee.