GLM-5.3: pricing, context and performance

Overview

Zhipu AI (Z.ai) released GLM-5.3 on August 14, 2026. It has a reasoning mode: it can "think" before answering, which helps with multi-step problems but uses more tokens, and therefore more money. It is an open-weight model: you can host it yourself on infrastructure you control, and 88 API providers listed on models.dev also offer it. That makes it 2 months old as of October 22, 2026.

We file it under open-weight models (68 models in this category on the site).

What do independent benchmarks say?

According to results published by Epoch AI (checked on October 22, 2026), GLM-5.3 has a capability index of 78.8 out of 100, computed on 5 benchmarks from our basket.

It is not among the top 30 of the weekly ranking.

• GPQA Diamond (PhD-level science questions): 90.9% — the best tracked model, Gemini 4 Argon, reaches 96.4%
• OTIS Mock AIME (competition mathematics problems): 91.1% — the best tracked model, GPT-5.5 Pro, reaches 100%
• FrontierMath (very hard research-level mathematics): 68.8% — the best tracked model, GPT-6 Astra, reaches 93.7%
• FrontierCode (advanced programming tasks): 40.1% — the best tracked model, Claude Opus 5.5, reaches 54.6%

Context and capabilities

Its context window reaches 1,000,000 tokens, roughly 1,500 pages of text at 500 words per page: enough to load a whole book or a mid-sized codebase. A single answer can run to 131,072 tokens.

It accepts as input: text.

It can call tools (functions, APIs) and return structured JSON output, which makes it a possible foundation for an AI agent.

The weights are published on Hugging Face (zai-org/GLM-5.3): 753.3 billion parameters, other license and 1,937,342 downloads over the last 30 days. See also our list of open-source models.

How much does GLM-5.3 cost?

GLM-5.3 costs $1.2 per million input tokens and $4.18 per million output tokens (developer's price, checked on October 22, 2026).

In practice, an agent task that reads 20,000 tokens and writes 2,000 costs about $0.032, or $32.27 for 1,000 such tasks.

That is 4.2 times the median output price of open-weight models ($1).

Tokens read back from cache cost $0.30 per million, which helps an agent that keeps resending the same context.

To estimate your own budget, use the agent cost calculator.

When to choose it

Given its category, GLM-5.3 is mainly aimed at projects where you want control over your data or hosting, or want to adapt the model to your field.

Its very large context window makes it worth considering for analysing large sets of documents in a single request.

Before adopting it, test it on your own examples: benchmarks measure standard tasks, not your job.

Comparable models

In the same category, the models closest to GLM-5.3 are:

• Kimi K2.5 (Moonshot AI, index 78.1) — see the comparison
• GLM-5 (Zhipu AI (Z.ai), index 77.2) — see the comparison
• Kimi K3 (Moonshot AI, index 80.7) — see the comparison
• Muse Spark Open (Meta, index 75.2) — see the comparison