Model comparison

GPT-5.4 Nano vs MiMo-V2.6-Pro

Pricing, context window and real answers (September 2026)

GPT-5.4 Nano (OpenAI) and MiMo-V2.6-Pro (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

openai logoGPT-5.4 NanoMiMo-V2.6-Pro
ProviderOpenAIXiaomi
Input (per 1M tokens)¥35.74¥77.73
Output (per 1M tokens)¥223.38¥155.47
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥147¥155
Context window400,000 tokens1,048,576 tokens
Release date3/17/20269/21/2026
Input modalitiesfile, image, texttext, image, video, audio
Throughput (p50)
Arena · overall#146 · ELO 1,402Unranked
Arena · Japanese#107 · ELO 1,368Unranked
Arena · coding#128 · ELO 1,460Unranked

Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.

Which should you pick?

  • On price, MiMo-V2.6-Pro: ¥155.47 per 1M output tokens, 30% less than GPT-5.4 Nano.
  • For long documents, MiMo-V2.6-Pro: a 1,048,576-token context window against 400,000 for GPT-5.4 Nano.
  • 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.

GPT-5.4 Nano

**Step 1:** Write the word: **strawberry** **Step 2:** Count each letter **r** in the word: - s **t r** a w b e **r r** y There are **3** **r**’s in total (**one** after the **t**, and **two** near the end). ✅ **Answer: 3**
1.5s86 output tokens

MiMo-V2.6-Pro

# Counting the 'r's in "strawberry" ## Step 1: Spell out the word letter by letter | Position | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | |----------|---|---|---|---|---|---|---|---|---|----| | Letter | s | t | r | a | w | b | e | r | r | y | ## Step 2: Identify every 'r' - **Position 3** → **r** ✅ (1st 'r') - **Position 8** → **r** ✅ (2nd 'r') - **Position 9** → **r** ✅ (3rd 'r') All other letters (s, t, a, w, b, e, y) are not 'r'. ## Answer There are **3** 'r's in "strawberry."
22.0s327 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…

GPT-5.4 Nano

This error means that **`users` is `undefined` (or otherwise not an array)** when your component renders, so calling `users.map(...)` throws: ```js users.map(...) ^^^^ reading 'map' of undefined ``` ### Why it happens Common causes: - You render `<UserList />` before data has loaded (e.g., `users` comes from an async fetch). - The parent component passes the wrong prop name (e.g., `user` instead of `users`). - The API/parent state initializes `users` as `undefined` rather than `[]`. - You’re destructuring a prop incorrectly upstream. ### Fix options #### 1) Ensure `users` is always an array (recommended) Initialize/default it in the component: ```js function UserList({ users = []…
3.3s383 output tokens

MiMo-V2.6-Pro

# Fixing `Cannot read properties of undefined (reading 'map')` ## The Problem The `users` prop is `undefined` when the component renders. This happens because `.map()` is being called on something that doesn't exist — JavaScript can't iterate over `undefined`. This typically occurs when: - The parent component doesn't pass the `users` prop at all - The data is still loading (e.g., from an API call) - A destructuring default doesn't exist ## The Fix ### Option 1: Provide a default value (simplest) ```jsx function UserList({ users = [] }) { return ( <ul> {users.map(user => <li key={user.id}>{user.name}</li>)} </ul> ); } ``` ### Option 2: Add a safety check with conditi…
32.9s575 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):…

GPT-5.4 Nano

Here are key improvements (readability, performance, robustness, best practices) and a revised version of your function. ## What to improve 1. **Avoid bare `except:`** Catch specific exceptions from `requests` (e.g., `requests.exceptions.RequestException`) to avoid hiding bugs. 2. **Prefer `raise_for_status()` or check status codes clearly** `r.raise_for_status()` is a common pattern. 3. **Use exponential backoff (or at least a clear retry delay)** Instead of sleeping the same amount every time, consider increasing delay. 4. **Reuse a `requests.Session()` (optional but best practice)** If this function is called repeatedly, passing a session or creating one outside i…
4.4s718 output tokens

MiMo-V2.6-Pro

# Code Review: `get_data` Function ## Issues Identified Here's my review organized by category, with a final improved version at the end. --- ### 🔴 Best Practices 1. **Imports inside the function** — `import requests` and `import time` are executed on *every* call. Move them to the top of the file (module-level). 2. **Bare `except:`** — This catches *everything*, including `KeyboardInterrupt` and `SystemExit`. Always catch specific exceptions. 3. **`== True` comparison** — Verbose and unnecessary. Use the object's truthiness directly. 4. **No logging** — Silent failures make debugging nearly impossible. 5. **Magic numbers** — `timeout=10` and `time.sleep(2)` are unexplained constan…
42.5s983 output tokens

Compare on more prompts →

Frequently asked questions

Which is cheaper, GPT-5.4 Nano or MiMo-V2.6-Pro?
Per 1M output tokens, GPT-5.4 Nano is ¥223.38 and MiMo-V2.6-Pro is ¥155.47 on FastMetal (yen, before tax), so MiMo-V2.6-Pro is cheaper.
How do the context windows of GPT-5.4 Nano and MiMo-V2.6-Pro compare?
GPT-5.4 Nano takes 400,000 tokens; MiMo-V2.6-Pro takes 1,048,576.
Can I use GPT-5.4 Nano and MiMo-V2.6-Pro with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-5.4-nano" or "mimo-v2.6-pro" 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 GPT-5.4 Nano and MiMo-V2.6-Pro from the browser chat and the API. No monthly fee.

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