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Z.ai · GLM · Balanced

GLM 5.3

Discount −82%New

Z.ai's general model for coding help, reasoning, writing and translation, with a 1M context window.

Model id

glm-5.3

Price per 1M tokens

Input
Regular rate $1.40now $0.396
Output
Regular rate $4.40now $0.77
Cached input
$0.2634% below input

82% below the market rate.

Added here 18 Oct 2026 — read the changelog for what changed and why.

Output is 1.9× the input rate. $1 covers about 1,282 prompts of 1,000 input + 500 output tokens. 1 credit = $1 of usage. All rates

Start using GLM 5.3

Set ONEAIAPIKEY_API_KEY to a key from your console, then run any example. Streaming is on so long answers are not cut off by idle-connection timeouts.

curl https://api.oneaiapikey.com/v1/chat/completions \
  -H "Authorization: Bearer $ONEAIAPIKEY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.3",
    "stream": true,
    "messages": [{"role": "user", "content": "Fix the off-by-one error in paginate() and add a test for the last page."}]
  }'
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.oneaiapikey.com/v1",
    api_key=os.environ["ONEAIAPIKEY_API_KEY"],
)

stream = client.chat.completions.create(
    model="glm-5.3",
    messages=[{"role": "user", "content": "Fix the off-by-one error in paginate() and add a test for the last page."}],
    stream=True,  # recommended for long outputs
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.oneaiapikey.com/v1",
  apiKey: process.env.ONEAIAPIKEY_API_KEY,
});

const stream = await client.chat.completions.create({
  model: "glm-5.3",
  messages: [{ role: "user", content: "Fix the off-by-one error in paginate() and add a test for the last page." }],
  stream: true,
});

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
}

More: quickstart · API reference · try it in Chat first

Benchmarks reported by the vendor

Scores for GLM 5.3 as its maker published them, with the setting they state. We have not re-run them. Versions and settings differ between vendors, so compare only identical benchmark names; compare models side by side.

Tokens per day, by model

Last 7 days, UTC days

Hover, tap or drag across any day, or focus the chart and use the arrow keys, to see how every model did that day.

Real tokens served through this gateway, updated every 5 minutes. Ranked by usage, not quality.

Full ranking insights

GLM line-up

GLM 5.3 or GLM 5.3 Flash or DeepSeek V4 Pro (free lane)?

Of the 2 GLM models on this site, GLM 5.3 is the top of the line-up and GLM 5.3 Flash the step down. DeepSeek V4 Pro (free lane) from DeepSeek is the closest-priced balanced-tier model from another vendor. Each comparison lists the published rates and limits, then what favours each side.

GLM 5.3vsGLM 5.3 Flash

Per 1M tokensGLM 5.3GLM 5.3 Flash
Input$0.3965.7× as much$0.07
Output$0.773.7× as much$0.21
Cached input$0.268.7× as much$0.03

Pick GLM 5.3 when

  • the task needs a higher tier: this catalogue places GLM 5.3 in the balanced tier and GLM 5.3 Flash in the fast tier.
  • you rely on Reasoning, which GLM 5.3 Flash does not list.
  • the work is coding help, writing and translation, which this catalogue lists for GLM 5.3 and not for GLM 5.3 Flash.

Pick GLM 5.3 Flash instead when

  • the job runs well enough on the lower rates: input at 82% less and output at 73% less.
  • your workload looks like quick answers, drafting and sub-agents, labels the catalogue gives GLM 5.3 Flash only.

GLM 5.3vsDeepSeek V4 Pro (free lane)

Per 1M tokensGLM 5.3DeepSeek V4 Pro (free lane)
Input$0.39619% less$0.49
Output$0.7721% less$0.98
Context1.02M2% larger1M
Max output128k67% less384k

Pick GLM 5.3 when

  • cost per request decides it: GLM 5.3 charges input 19% less and output 21% less than DeepSeek V4 Pro (free lane).
  • prompts run past 1M tokens: GLM 5.3 reads up to 1.02M.
  • you rely on Prompt caching, which DeepSeek V4 Pro (free lane) does not list.
  • the work is coding help, writing and translation, which this catalogue lists for GLM 5.3 and not for DeepSeek V4 Pro (free lane).

Pick DeepSeek V4 Pro (free lane) instead when

  • the 128k output cap of GLM 5.3 cuts answers short; DeepSeek V4 Pro (free lane) writes up to 384k.
  • your workload looks like coding agents, hard reasoning and math, labels the catalogue gives DeepSeek V4 Pro (free lane) only.

Use cases

What GLM 5.3 is listed for, and what it costs

The catalogue lists GLM 5.3 for coding help, writing and translation. Each row prices one typical request at the published rates, with the arithmetic shown. The market-rate figure shows the same request at the lowest public price elsewhere. Token counts are examples; your prompts will differ.

Model your own traffic

  1. Coding help

    A bug fix or small feature: 12,000 tokens of the relevant files in, a patch of about 1,500 tokens out.

    “Fix the off-by-one error in paginate() and add a test for the last page.”

    Same request on GLM 5.3 Flash $0.001156 and DeepSeek V4 Pro (free lane) $0.00735.

    $0.005906

    per change, about 1,693 per $10

    $0.0234 at the market rate

    0.012 × $0.396 + 0.0015 × $0.77

  2. Writing

    A brief plus source notes: 3,000 tokens in, a draft of roughly 1,200 words (1,600 tokens) out.

    Provide tone, audience and length; it follows style instructions closely.

    “Turn these release notes into a 300-word changelog post for developers.”

    Same request on GLM 5.3 Flash $0.000546 and DeepSeek V4 Pro (free lane) $0.003038.

    $0.00242

    per draft, about 4,132 per $10

    $0.01124 at the market rate

    0.003 × $0.396 + 0.0016 × $0.77

  3. Translation

    A document of about 1,500 words translated: 2,200 tokens in, 2,400 tokens out.

    “Translate this support article into Spanish, keeping the headings and code blocks unchanged.”

    Same request on GLM 5.3 Flash $0.000658 and DeepSeek V4 Pro (free lane) $0.00343.

    $0.00272

    per document, about 3,676 per $10

    $0.01364 at the market rate

    0.0022 × $0.396 + 0.0024 × $0.77

Overview

When GLM 5.3 fits

GLM 5.3 is a balanced model from Z.ai, available here under the exact model id “glm-5.3”. It heads the GLM line-up here, above GLM 5.3 Flash. Z.ai has not published a release date we can cite; it has been available here since 18 Oct 2026.

Z.ai documents tools, reasoning, json mode and prompt caching for it.

It costs $0.396 per million input tokens and $0.77 per million output tokens, so output is 1.9× the input rate. That is 82% below the market rate of $1.40 input and $4.40 output per million tokens, the lowest public price we found at other API gateways. On the use cases below, output makes up 20% of the bill for coding help, 51% for writing and 68% for translation, so capping max tokens and asking for diffs saves more than trimming the prompt. With a 3:1 input-to-output mix it ranks 8th lowest-cost of the 27 models on this site.

Cached input bills at $0.26 per million tokens, 34% below the standard input rate, which pays off when the same system prompt or documents go out on every request.

It is served through the OpenAI-compatible format at https://api.oneaiapikey.com/v1, so any SDK or tool that lets you set a custom base URL, for example Codex CLI, Cursor and Cline, can use it. It is not offered on the Anthropic Messages endpoint; pick an Anthropic-format model for Claude Code.

Use GLM 5.3 with any balance.

GLM 5.3 is a paid model: any balance above $0 pays for it, the $10.00 sign-up credit included. When it runs out, add $1 or more to your wallet. Every request is billed at the rates above, with a receipt in your usage log.

GLM 5.3 is developed by Z.ai. Model names and trademarks belong to their owners. One AI API Key is an independent API gateway and is not affiliated with, endorsed by or sponsored by Z.ai.