Z.ai / MODEL PROFILE

GLM 5.3

A large GLM checkpoint for coding, with a separate license from Flash.

Data sourcesPublisher specificationsCalculated memory estimatesSource review · Sep 22, 2026
Published size
~753B*
Active parameters
See model card
Context window
Under review
Architecture
MoE
License
GLM-5.3 License
THE DEPLOYMENT PERSPECTIVE

Deployment considerations

Check this release's license and deployment recipe directly. Do not inherit the license or memory requirements of GLM 5.3 Flash.

01

The approximately 753B figure is the repository's displayed tensor count, pending reconciliation with the architecture. Memory estimates remain unavailable.

02

GPU memory estimates and minimum / recommended configurations are pending. This profile does not contain measured deployment results.

Verify against the upstream model card
DEPLOYMENT CONFIGURATIONPENDING

GPU requirements

Minimum
GPU / VRAM · pending

Memory estimates and tested configurations will appear here after checkpoint review and deployment testing.

THE MEASURED PART COMES NEXT

No invented leaderboards.

Latency, throughput, and cost per token will appear here after a reproducible run. Until then, this page helps you understand the model—not predict its performance.

Read our protocol
A FEW USEFUL ANSWERS

GLM 5.3 deployment FAQ

How much GPU memory does GLM 5.3 need?

The full checkpoint weight footprint is pending review. Minimum and recommended GPU configurations will be added after testing; the model name or active parameter count alone is not a memory requirement.

Has BenchGrid benchmarked GLM 5.3?

Not yet. This profile contains publisher specifications and calculated weight-memory estimates. We do not currently publish measured latency, throughput, or cost per token for this model.

Where do these specifications come from?

The specifications are based on the official Z.ai model card linked on this page. Memory estimates use the stated total parameter count, including inactive experts for MoE models. Nominal model sizes are labeled with ~.

WHEN YOU’RE READY TO EXPERIMENT

Explore your compute options.

Check available hardware, quotas, and current pricing with the provider. These links are not verified deployments or performance recommendations.