How much does the GLM 5.3 FlashX API cost?

On FastMetal, GLM 5.3 FlashX is billed per token in yen: ¥66.12 per 1M input tokens and ¥223.38 per 1M output tokens, before tax. Usage is drawn from a prepaid balance; there is no subscription or monthly fee.

Can I call GLM 5.3 FlashX with the OpenAI SDK?

Yes. Point base_url at https://api.fastmetal.ai/v1 and pass "glm-5.3-flashx" as the model; existing OpenAI-style code works unchanged, including streaming, tool calls and structured output.

What is the context window of GLM 5.3 FlashX?

1,048,576 tokens, shared between the prompt and the response.

What do I need to try GLM 5.3 FlashX?

Create an account and add credit; the model is then available both in the browser chat and over the API. There is no contract or minimum spend.

Back to Models

z-ai/glm-5-3-flashx

GLM 5.3 FlashX

GLM-5.3-FlashX is the high-speed variant of Z.ai's GLM-5.3-Flash, a native multimodal model delivering inference speeds of up to 200 tokens/s. Built on the same hybrid sparse and linear attention architecture...

9/18/2026

1,048,576 tokens

Input: ¥66.119/M

Output: ¥223.375/M

Try in Chat Get API Key

Specifications

Modalities

Input

text

image

video

Output

text

Supported Parameters

include_reasoning

max_tokens

reasoning

reasoning_effort

response_format

temperature

tool_choice

tools

top_k

top_p

Max Output Tokens

131,072

Reasoning Configuration

Default: Thinking on (effort: max)
Selectable effort levels: max
high
low
Turning thinking off: Not possible (always thinks)

How to control thinking, and what it costs

Data policy

Prompt retention: Unknown — we could not confirm
Training: Not used for training

"Unknown" does not mean "safe". It means we could not confirm it.

Whether a provider trains on prompts is a declared value from our terms with them. Retention is determined from the upstream listing for every host this model can reach. Neither is guessed.

Code Examples

curl https://api.fastmetal.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "glm-5.3-flashx",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

How GLM 5.3 FlashX actually answers

Real responses to our standard prompts, recorded on FastMetal.

Count the number of 'r's in 'strawberry'

Count the number of 'r's in 'strawberry'. Explain your reasoning step by step.

# 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…

4.1s response549 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…

## 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>…

6.8s response934 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):…

# 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…

36.9s response5836 output tokens

Compare these answers side by side with other models →

Frequently asked questions

How much does the GLM 5.3 FlashX API cost?: On FastMetal, GLM 5.3 FlashX is billed per token in yen: ¥66.12 per 1M input tokens and ¥223.38 per 1M output tokens, before tax. Usage is drawn from a prepaid balance; there is no subscription or monthly fee.
Can I call GLM 5.3 FlashX with the OpenAI SDK?: Yes. Point base_url at https://api.fastmetal.ai/v1 and pass "glm-5.3-flashx" as the model; existing OpenAI-style code works unchanged, including streaming, tool calls and structured output.
What is the context window of GLM 5.3 FlashX?: 1,048,576 tokens, shared between the prompt and the response.
What do I need to try GLM 5.3 FlashX?: Create an account and add credit; the model is then available both in the browser chat and over the API. There is no contract or minimum spend.