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chatglm
z-ai/glm-5.3

z-ai/glm-5.3

Release date: 2026-08-19

1,310,720 context · $1.40/M input tokens · $4.40/M output tokens

GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves...

Pricing

Pay-per-use

No upfront costs, pay only for what you use

Input$1.40 / M Tokens
Output$4.40 / M Tokens
Cache Read$0.26 / M Tokens

Try the model

z-ai/glm-5.3
Online
chatglm
Hi! I am a helpful AI assistant. What can I do for you?
Ready to use this model in a local coding agent?Agent Setup

API Usage

Use the following code examples to integrate with our API:

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 0,
});

try {
  const response = await client.chat.completions.create({
    model: 'z-ai/glm-5.3',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  const body = response as typeof response & { error?: { message?: string } };
  if (body.error) throw new Error(body.error.message || 'LLM generation failed');
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

Model Introduction

Z.ai: GLM 5.3

GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves...

This model is imported from OpenRouter metadata and exposed through the WaveSpeed AI OpenAI-compatible API for chat completions and compatible application workflows.


Why It Looks Great

  • text->text architecture for Text to Text workloads
  • 1310720 context window for long prompts, document analysis, and multi-turn workflows
  • Competitive pricing at $1.4/$4.4 per million tokens
  • Function calling and tool-use support for agentic application workflows
  • Structured output support for JSON responses and schema-constrained generation
  • Reasoning controls available through supported OpenRouter parameters

Key Features

  • Context Window: 1310720 tokens
  • Max Input: 367003 tokens
  • Max Output: 943717 tokens
  • Vision: Not listed
  • Function Calling: Supported
  • Structured Outputs: Supported
  • Image Generation: Not listed
  • Audio Input: Not listed
  • Supported Parameters: frequency_penalty, include_reasoning, logit_bias, logprobs, max_tokens, min_p, parallel_tool_calls, presence_penalty, reasoning, reasoning_effort, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p

Specifications

SpecificationValue
Providerchatglm
Model TypeChat Completions model
Architecturetext->text
Context Window1310720 tokens
Max Input367003 tokens
Max Output943717 tokens
InputText
OutputText
VisionNot listed
Function CallingSupported
Structured OutputsSupported
OpenRouter CreatedAugust 19, 2026

Pricing

Token TypeCost
Input$1.4 per million tokens
Output$4.4 per million tokens
Cached Input$0.26 per million tokens

Note: Pricing is generated from OpenRouter model metadata. If multiple upstream providers expose different endpoint prices, review and adjust the price before publishing.


How to Use

  1. Write your prompt - describe the task, provide context, and specify the desired output format.
  2. Submit - the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: z-ai/glm-5.3


API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="z-ai/glm-5.3",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)

cURL

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

Notes

  • Model: z-ai/glm-5.3
  • Provider: chatglm
  • Endpoint availability and provider-specific routing may change on OpenRouter

Sources: OpenRouter model metadata.

Info

Providerchatglm
Typellm

Supported Functionality

Input
Text
Output
Text
Context1,310,720
Max Output943,717
Vision-
Function Calling✓ Supported

API Access Guide

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
Model IDz-ai/glm-5.3

GLM 5.3 API

z-ai/glm-5.3

GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves...

Input

$1.4 /M

Output

$4.4 /M

Context

1311K

Max Output

944K

Tool Use

Supported

Try GLM 5.3 on WaveSpeedAI

Access GLM 5.3 through our unified API — OpenAI-compatible, no cold starts, transparent pricing.

Frequently Asked Questions about GLM 5.3

How much does GLM 5.3 cost via the API?+

Pricing on WaveSpeedAI: $1.40 per million input tokens and $4.40 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.

What is the context window of GLM 5.3?+

GLM 5.3 supports up to 1311K tokens of context with up to 944K tokens of output per request.

Is GLM 5.3 OpenAI-compatible?+

WaveSpeedAI exposes GLM 5.3 at https://llm.wavespeed.ai/v1 through the OpenAI-compatible Chat Completions interface. Most OpenAI SDK clients work by changing the base URL and API key; optional fields depend on the selected model.

How do I get started with GLM 5.3?+

Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with the model id shown above. Check the current model catalog for availability, capabilities, and pricing.

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