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// GLM / CogVideoX (Z.ai) · Video generation

SCAIL-2: VRAM & local deployment

Video generation model published by Z.ai (Zhipu).

released 2026-06-09licence: Commercial OKmemory figures are estimates

01Specs

PublisherZ.ai (Zhipu) · zai-org
Family / seriesGLM / CogVideoX (Z.ai) · SCAIL-2
TypeVideo generation (image-to-video)
Parametersnot stated in official metadata
LicenceMIT · Commercial OKPermissive licence (Apache-2.0 / MIT / CC-BY / OpenMDW): commercial use allowed.
Released2026-06-09 (Hugging Face repo created)

02How much VRAM it needs (estimate)

Video models: memory grows with resolution and clip length; official repos usually list a tested GPU in the card. Weights below are the main model only.

No estimate: the official metadata does not give a parameter count. Check the model card for tested hardware.

Bits per weight: BF16 16, FP8 8.5, 4-bit 4.85. “Fits” = total ≤ 90% of memory; Mac GPU can use ~2/3 of unified memory (≤36GB) or ~3/4 (larger). For MoE, all experts must be in memory, so size by total parameters. Method →

03How to run it

Only runtimes the publisher or the runtime’s official library names for this model.

The official card does not name a runtime; see the repository.

Which inference engine to choose →

04Official repositories & quantised builds

1 official repo(s) from zai-org.

05Other GLM / CogVideoX (Z.ai) models

All 35 →
ModelParams4-bit totalReleased
GLM-5.3753.3B504 GB2026-08-25
GLM-5.3-Flash320B / 18B214 GB2026-08-25
GLM-5.2753.3B504 GB2026-06-16
GLM-5.1753.9B504 GB2026-04-03
GLM-5744B / 40B497 GB2026-02-11
GLM-OCR1.32B1.9 GB2026-01-30
GLM-4.7-Flash31.2B / 3B21.8 GB2026-01-19
GLM-Image6.93B5.1 GB2026-01-08

06Sources

Data checked 2026-07-15. Parameters, context and licence are copied from the official repository; memory figures are our estimates.

Data updated: Self-host open models(UTC+8)