After a stunning debut last week with cyber capabilities so advanced they reportedly found a previously undetected vulnerability in Cursor, GLM-5.3, the new frontier open source language model from Chinese startup z.ai, has now hit the application programming interface (API) — allowing developers the ability to build atop it and plug it into their agents and applications.

Developers who previously subscribed to a GLM Coding Plan are currently limited to the OpenAI Chat Completions-compatible protocol. Z.ai said it plans to make the model’s weights openly available, but a precise date and licensing remain to be seen.

On the API, the price is unchanged from GLM-5.2: $1.40 per million input tokens and $4.40 per million output tokens. Cached input costs $0.26 per million tokens, while Z.ai currently lists cached-input storage as free for a limited time.

That means developers can move to the new generation without taking a higher posted per-token rate from Z.ai, even as the company claims substantially stronger coding and long-horizon agent performance.
At those rates, GLM-5.3 sits well below several of the highest-end frontier APIs.

Using the simple VentureBeat comparison of one million input tokens plus one million output tokens, GLM-5.3 comes to $5.80, versus $8 for Grok 4.6 at its lower context rate, $18 for Kimi K3, $30 for Claude Opus 5 and $35 for GPT-5.6 Sol.

That is not a workload-cost estimate — real bills depend heavily on the input/output mix, caching and token consumption — but it makes the relative API price tier easy to see.

GLM-5.3 is not the cheapest capable model available. Google’s current introductory price for Gemini 3.7 Flash is $0.75 per million input tokens and $3.75 per million output tokens through Dec. 31, 2026, while OpenAI’s GPT-5.6 Luna is priced at $0.20 input and $1.20 output.

Still, Z.ai’s price puts GLM-5.3 into a notably lower cost band than the premium frontier models it is increasingly benchmarked against.

That comparison has become more relevant following the latest independent results. Artificial Analysis gives GLM-5.3 a score of 60 on its Intelligence Index, tying Kimi K3 as the top performing open weights model in the world, and scoring seven points higher than GLM-5.2. I

ts analysis also estimates GLM-5.3 at about $0.68 per Intelligence Index task, versus roughly $0.44 for GLM-5.2, despite the identical API token prices.

The difference underscores an important caveat in headline API pricing: Artificial Analysis found GLM-5.3 more verbose than its predecessor, so flat per-token rates do not necessarily mean flat costs for a completed workload.

For developers, though, the immediate change is straightforward: GLM-5.3 is now callable through Z.ai’s API at the same $1.40/$4.40 per-million-token rate as GLM-5.2, giving teams another relatively low-cost option for testing frontier-class coding and agent workloads.