Model comparison

DeepSeek V4.1 Flash vs GLM 5.3 FlashX

Pricing, context window and real answers (September 2026)

DeepSeek V4.1 Flash (DeepSeek) and GLM 5.3 FlashX (Z.ai), 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

deepseek logoDeepSeek V4.1 Flashz-ai logoGLM 5.3 FlashX
ProviderDeepSeekZ.ai
Input (per 1M tokens)¥36.96¥66.12
Output (per 1M tokens)¥110.88¥223.38
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥92¥178
Context window1,048,576 tokens1,048,576 tokens
Release date9/10/20269/18/2026
Input modalitiestext, imagetext, image, video
Throughput (p50)
Arena · overallUnrankedUnranked
Arena · JapaneseUnrankedUnranked
Arena · codingUnrankedUnranked

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

Which should you pick?

  • On price, DeepSeek V4.1 Flash: ¥110.88 per 1M output tokens, 50% less than 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.

DeepSeek V4.1 Flash

The word **“strawberry”** has **3** letter **“r”**s. Step-by-step: 1. Spell it out: **s t r a w b e r r y** 2. Find each **r**: - Position 3: **r** in “str” - Position 8: first **r** in “berry” - Position 9: second **r** in “berry” 3. Total: **3** **Answer: 3**
7.5s226 output tokens

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

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…

DeepSeek V4.1 Flash

The error means that `users` is `undefined` when `UserList` renders, so JavaScript cannot call `.map()` on it. Your component expects a `users` prop: ```jsx function UserList({ users }) { return ( <ul> {users.map(user => <li key={user.id}>{user.name}</li>)} </ul> ); } ``` But it is being rendered without `users`, or `users` has not loaded yet. Common causes: 1. Parent renders it without the prop: ```jsx <UserList /> ``` instead of: ```jsx <UserList users={users} /> ``` 2. The prop name is different: ```jsx <UserList userList={users} /> ``` 3. The data is fetched asynchronously and is initially `undefined`: ```jsx const [users, setUsers] = useState(); useEffect(…
16.0s945 output tokens

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

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):…

DeepSeek V4.1 Flash

Here are the main improvements: - Move imports to module level. - Avoid bare `except`; catch specific exceptions. - Use a `requests.Session` for connection reuse. - Retry only transient network/HTTP failures, not all errors. - Use exponential backoff and don’t sleep after the final attempt. - Use a list comprehension for readability/performance. - Add type hints, logging, constants, and basic JSON validation. - Avoid `== True`; use `is True` or a truthy check depending on API contract. Example refactor: ```python from __future__ import annotations import logging import time from typing import Any import requests logger = logging.getLogger(__name__) TIMEOUT = (3.05, 10) # connect time…
31.5s5142 output tokens

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

Compare on more prompts →

Frequently asked questions

Which is cheaper, DeepSeek V4.1 Flash or GLM 5.3 FlashX?
Per 1M output tokens, DeepSeek V4.1 Flash is ¥110.88 and GLM 5.3 FlashX is ¥223.38 on FastMetal (yen, before tax), so DeepSeek V4.1 Flash is cheaper.
How do the context windows of DeepSeek V4.1 Flash and GLM 5.3 FlashX compare?
DeepSeek V4.1 Flash takes 1,048,576 tokens; GLM 5.3 FlashX takes 1,048,576.
Can I use DeepSeek V4.1 Flash and GLM 5.3 FlashX with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4.1-flash" or "glm-5.3-flashx" 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 DeepSeek V4.1 Flash and GLM 5.3 FlashX from the browser chat and the API. No monthly fee.

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