Analysis Summary
GLM 5.3 is Z.ai's high-end model for demanding reasoning, coding, and agentic workflows. It combines strong measured performance across all three areas with tool use and function calling, while its 1.31M token context window supports entire codebases, lengthy contracts, and extensive research collections.
This profile fits autonomous software engineering, complex document analysis, SEO strategy, and client-facing content where consistency matters more than minimum cost. The text-only modality is less versatile than the Flash variant for visual or video work. Pricing of $1.40 per million input tokens and $4.40 per million output tokens makes selective routing sensible. Adopt it for high-value reasoning and coding tasks, then use a cheaper model for routine production volume.
Assessed September 1, 2026
Editorial notes
GLM 5.3 delivers advanced reasoning, strong coding and agentic performance, function calling, tool use, and a 1.31M token context window. Its text-only modality and higher pricing favour complex workflows over multimodal volume traffic.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
GLM 5.3 delivers advanced reasoning, strong coding and agentic performance, function calling, tool use, and a 1.31M token context window. Its text-only modality and higher pricing favour complex workflows over multimodal volume traffic.
How Z.ai: GLM 5.3 compares
Z.ai: GLM 5.3 ranks #8 of 433 AI models we track for overall intelligence, #13 of 206 for coding, #7 of 188 for agentic tasks. Its 1.3M-token context window is larger than 99% of the models we list. At $1.40 per million input tokens it is cheaper than 20% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on business fit. The pulled-in value corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $1.40 | $0.001400 |
| Output | $4.40 | $0.004400 |
What would Z.ai: GLM 5.3 cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 748 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Z.ai: GLM 5.3 for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout 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..
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<a href="https://designforonline.com/ai-models/z-ai-glm-5-3/"><img src="https://designforonline.com/?aiml_badge=z-ai-glm-5-3&theme=dark" alt="Z.ai: GLM 5.3, ranked #6 on the Design for Online AI Leaderboard" width="400" height="76"></a>
<a href="https://designforonline.com/ai-models/z-ai-glm-5-3/"><img src="https://designforonline.com/?aiml_badge=z-ai-glm-5-3&theme=light" alt="Z.ai: GLM 5.3, ranked #6 on the Design for Online AI Leaderboard" width="400" height="76"></a>
Frequently asked questions about Z.ai: GLM 5.3
How much does Z.ai: GLM 5.3 cost?
Z.ai: GLM 5.3 costs $1.40 per million input tokens and $4.40 per million output tokens.
What is the context window of Z.ai: GLM 5.3?
Z.ai: GLM 5.3 has a context window of 1,310,720 tokens (1.3M).
Is Z.ai: GLM 5.3 good for coding?
On our coding benchmark index, Z.ai: GLM 5.3 ranks #13 of 206 models, placing it in the top quartile of the field for code generation and debugging.
What can Z.ai: GLM 5.3 do?
Z.ai: GLM 5.3 supports tool use and function calling.
Who created Z.ai: GLM 5.3?
Z.ai: GLM 5.3 is developed by Z.ai and was released on August 18, 2026.
Data sourced from the OpenRouter API, Artificial Analysis, the Hugging Face Open LLM Leaderboard and our own internal testing. Scores are editorially curated by our team.
Last updated: September 3, 2026 8:38 pm