Model comparison

GLM 5.1 vs MiMo-V2.5

Pricing, context window and real answers (August 2026)

GLM 5.1 (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

z-ai logoGLM 5.1MiMo-V2.5
ProviderZ.aiXiaomi
Input (per 1M tokens)¥250.18¥25.02
Output (per 1M tokens)¥786.28¥50.04
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥643¥50
Context window204,800 tokens1,050,000 tokens
Release date4/7/20264/22/2026
Input modalitiestexttext, audio, image, video
Arena · overall#41 · ELO 1,466#92 · ELO 1,434
Arena · Japanese#49 · ELO 1,430#137 · ELO 1,322
Arena · coding#36 · ELO 1,514#76 · 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, 94% less than GLM 5.1.
  • On the Overall arena board, GLM 5.1 ranks higher (#41; MiMo-V2.5 is #92).
  • On the Japanese arena board, GLM 5.1 ranks higher (#49; MiMo-V2.5 is #137).
  • On the Coding arena board, GLM 5.1 ranks higher (#36; MiMo-V2.5 is #76).
  • For long documents, MiMo-V2.5: a 1,050,000-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

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 5.1

### 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

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 5.1

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

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

Compare on more prompts →

Frequently asked questions

Which is cheaper, GLM 5.1 or MiMo-V2.5?
Per 1M output tokens, GLM 5.1 is ¥786.28 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 5.1 and MiMo-V2.5 compare?
GLM 5.1 takes 204,800 tokens; MiMo-V2.5 takes 1,050,000.
Which ranks higher, GLM 5.1 or MiMo-V2.5?
GLM 5.1 ranks higher on the public arena (GLM 5.1 #49, MiMo-V2.5 #137). Ranks move as the leaderboard updates.
Can I use GLM 5.1 and MiMo-V2.5 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.1" 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 5.1 and MiMo-V2.5 from the browser chat and the API. No monthly fee.

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