Model comparison

DeepSeek V4 Flash vs GLM 5.3 FlashX

Pricing, context window and real answers (September 2026)

DeepSeek V4 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 Flashz-ai logoGLM 5.3 FlashX
ProviderDeepSeekZ.ai
Input (per 1M tokens)¥24.61¥66.12
Output (per 1M tokens)¥49.21¥223.38
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥49¥178
Context window1,048,576 tokens1,048,576 tokens
Release date4/24/20269/18/2026
Input modalitiestexttext, image, video
Throughput (p50)
Arena · overall#92 · ELO 1,436Unranked
Arena · Japanese#78 · ELO 1,396Unranked
Arena · coding#92 · ELO 1,483Unranked

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 Flash: ¥49.21 per 1M output tokens, 78% 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 Flash

The word "strawberry" is spelled as s-t-r-a-w-b-e-r-r-y. I go through each letter: s (no), t (no), r (yes, first), a (no), w (no), b (no), e (no), r (yes, second), r (yes, third), y (no). Thus, there are three 'r's.
3.9s251 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 Flash

The error occurs because `users` is `undefined` when the component tries to call `.map()` on it. ## Why this happens Your component expects `users` to be an array, but it's receiving `undefined` as a prop. This typically happens when: 1. The parent component doesn't pass the `users` prop 2. The data fetching hasn't completed yet (async data loading) 3. The API response is missing the expected data structure ## How to fix it ### Option 1: Default prop value (Recommended for initial state) ```jsx function UserList({ users = [] }) { return ( <ul> {users.map(user => <li key={user.id}>{user.name}</li>)} </ul> ); } ``` ### Option 2: Guard clause (More explicit) ```jsx func…
6.3s422 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 Flash

Here's a comprehensive review with suggested improvements: ## Issues Identified: 1. **Import at wrong location** - Imports inside functions are inefficient and non-standard 2. **Bare `except:` clause** - Catches all exceptions including `KeyboardInterrupt`, `SystemExit` 3. **Missing error handling granularity** - Should distinguish between retryable and non-retryable errors 4. **Duplicate sleep logic** - Same sleep in `else` and `except` blocks 5. **Unnecessary variable** - `data` is only used once 6. **Inefficient list building** - Manual loop instead of list comprehension 7. **Hardcoded error message** - No logging or error context 8. **Missing type hints** - No type annotations 9. **Fun…
12.6s987 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

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Frequently asked questions

Which is cheaper, DeepSeek V4 Flash or GLM 5.3 FlashX?
Per 1M output tokens, DeepSeek V4 Flash is ¥49.21 and GLM 5.3 FlashX is ¥223.38 on FastMetal (yen, before tax), so DeepSeek V4 Flash is cheaper.
How do the context windows of DeepSeek V4 Flash and GLM 5.3 FlashX compare?
DeepSeek V4 Flash takes 1,048,576 tokens; GLM 5.3 FlashX takes 1,048,576.
Can I use DeepSeek V4 Flash and GLM 5.3 FlashX with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4-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 Flash and GLM 5.3 FlashX from the browser chat and the API. No monthly fee.

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