Zhipu AI: GLM 5.3

Name: GLM 5.3
Brand: Zhipu AI
Price: 1.20 USD
Availability: InStock

GLM 5.3 is Zhipu AI's large-scale reasoning model, released 2026-08, built for complex software engineering and long-horizon agent tasks. It improves on GLM-5.2 in coding and in the balance between performance and token efficiency, with reasoning always on and optimized for extended autonomous work.

Modalities

inTextoutText

Price / 1M−7%

$1.20 / $4.20~~$1.40 / $4.40~~

Context

1.049M

Knowledge cutoff

—

Capabilities

ReasoningTool useLong contextPrompt cachingStructured output

Channels

Same weights on every channel. Requests route to the cheapest healthy one; the channel used is printed on each billing line.

Provider

Discount

Input /M

Output /M

Cache Read /M

Cache Create 5m /M

Cache Create 1h /M

Defaultstable

−7%

$1.20

$4.20

$0.26

—

Cost Calculator

Pick a channel and a usage scenario, then drag to your workload — each scenario assumes a different prompt-cache hit rate.

Channel

Scenario

Input tokens / request1,600Output tokens / request800Requests / month60,000

Unit $1.20 / $4.20 /1MDaily chat: 40% cache hit assumed · cache read $0.26 /1M

List price ~~$303.49~~On MirAPI$280.70/ moYou save $22.78Create an API key

Benchmarks

bar = score (0–100) · ▏ median

Scores from vendor reports and public leaderboards. No private evals.

Intelligence Index

General ability

59.5

Coding Index

Code

74.8

Agentic Index

Agentic

59.1

Showcase

Three fixed prompts, identical for every chat model. Outputs are archived verbatim — copy the prompt to reproduce.

Task prompt · identical for all models

Build a single-file HTML page using three.js from a CDN: a low-poly planet with a tilted ring of ~200 orbiting particles, a soft key light plus rim light, slow auto-rotation, and drag-to-orbit controls. No build tools — one file only.

Run in Playground

Archived output

Archive not published yet

Every model will run this exact prompt; the output lands here verbatim, with tokens and per-run cost.

Quick Start

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.mirapi.ai/v1",   # changed
    api_key=os.environ["MIRAPI_API_KEY"],   # changed
)

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

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.mirapi.ai/v1",  // changed
  apiKey: process.env.MIRAPI_API_KEY,      // changed
});

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

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

# ~/.zshrc
export ANTHROPIC_BASE_URL="https://api.mirapi.ai"
export ANTHROPIC_AUTH_TOKEN="$MIRAPI_API_KEY"

# start as usual — model names unchanged
claude --model z-ai/glm-5.3

# ~/.codex/config.toml
model_provider = "mirapi"
model = "z-ai/glm-5.3"

[model_providers.mirapi]
name = "MirAPI"
base_url = "https://api.mirapi.ai/v1"
env_key = "MIRAPI_API_KEY"
wire_api = "responses"

Links

z.ai www.mirapi.ai

Wire GLM 5.3 into your product

1M free tokens to start · no card · OpenAI-compatible, one base_url change

Start free