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GLM 5.3

z-ai/glm-5.3

reasoningtool callingprompt caching

GLM 5.3 costs $0.070 per 1M input tokens and $1.40 per 1M output tokens with a 1.0M-token context window.

A reasoning, tool-calling model from z-ai, released Aug 18, 2026. LiveBench hasn't published a run for it, so this page carries measured price and specs only — no benchmark numbers.

Input / 1M
$0.070
Output / 1M
$1.40
Context
1.0M
LiveBench overall
Not evaluated

Specs and pricing

Input price

USD per 1M prompt tokens

$0.070
Output price

USD per 1M completion tokens, reasoning included

$1.40
Blended price

3:1 input:output — #125 cheapest of 350 listed models

$0.402
Cached input read

Blank means not priced separately — not free

$0.069
Cache write—
Context window1,048,576 tokens
Max output943,718 tokens
Input modalitiestext
Tool callingYes
Extended reasoningYes
Knowledge cutoff—
ListedAug 18, 2026
All Z.ai API pricing

Also listed as z-ai/glm-5.3:batch ($0.837 blended)— the same model at a different price or rate limit.

What GLM 5.3 costs to run

Monthly list cost across five workload shapes, using the published cached-input rate where there is one. A floor, not a quote — batch discounts and cache writes aren't included.

WorkloadPer month
Support chatbot

1.2K in / 400 out × 200K requests

$128.70/mo
RAG assistant

8K in / 600 out × 100K requests

$139.52/mo
Coding agent

40K in / 4K out × 20K requests

$167.36/mo
Document extraction

20K in / 1.5K out × 50K requests

$174.85/mo
Bulk classification

500 in / 20 out × 5M requests

$314.25/mo
Price your own workload

Compare GLM 5.3 with

Benchmarked models at a similar price.

Cheaper and stronger alternatives to GLM 5.3

GLM 5.3 FAQ

How much does GLM 5.3 cost?

GLM 5.3 lists at $0.070 per 1M input tokens and $1.40 per 1M output tokens, with cached input reads at $0.069 per 1M. A RAG assistant handling 100K requests a month (8K tokens in, 600 out) comes to about $139.52 at list price.

What is the context window of GLM 5.3?

GLM 5.3 accepts up to 1,048,576 tokens of context and can return up to 943,718 output tokens per response.

Does GLM 5.3 support tool calling?

Yes — GLM 5.3 supports tool (function) calling and exposes extended reasoning. It accepts text input.

How does GLM 5.3 score on benchmarks?

LiveBench has not published a run for GLM 5.3 yet. Until it does, compare it on price and specs, or run your own evaluation on your own tasks.

What is the API model ID for GLM 5.3?

On OpenRouter the model ID is "z-ai/glm-5.3". It was listed on Aug 18, 2026.

More from z-ai

How these numbers are produced

  • Price and specs — provider list data from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
  • Scores and ranks — LiveBench release 2026-10-25. Ranks count only models that have a published run; a blank means “not evaluated”, never “bad”.
  • Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.

Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.