Video models ·

CogVideoX 1.5 5B

Backbone
5.6B
Native output
1360×768, 81 frames
Default steps
50
License
cogvideox
Released
2024-11

How to run it

Original weights · Hugging Face

Full-precision files from Zhipu AI, for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/zai-org/CogVideoX1.5-5B (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Zhipu AI. The weights themselves download from Hugging Face.

github.com/zai-org/CogVideo (opens in a new tab)

git clone https://github.com/zai-org/CogVideo

Links checked 1 day ago against Hugging Face, Ollama and GitHub.

Apps that run CogVideoX 1.5 5B

Our pick for each kind of computer, assuming the model fits in its memory. Pick your own GPU or device in the Model Finder for an exact answer.

Mac (Apple silicon)

ComfyUI

Runs this model with built-in or popular custom nodes; GGUF files load with ComfyUI-GGUF.

Also good:

Windows PC, NVIDIA GPU

ComfyUI

Runs this model with built-in or popular custom nodes; GGUF files load with ComfyUI-GGUF.

Also good:

Linux, NVIDIA or AMD GPU

ComfyUI

Runs this model with built-in or popular custom nodes; GGUF files load with ComfyUI-GGUF.

Also good:

App Type Opens it as Systems Engine Start
ComfyUI Desktop app Built-in support macOSWindowsLinux PyTorch, GGUF via ComfyUI-GGUF Get ComfyUI
SwarmUI Desktop app Built-in support macOSWindowsLinux ComfyUI Get SwarmUI
SD.Next Desktop app Built-in support macOSWindowsLinux PyTorch Get SD.Next
Stability Matrix Desktop app Built-in support macOSWindowsLinux installs ComfyUI, Forge, InvokeAI, SwarmUI, SD.Next or Fooocus Get Stability Matrix

Which apps can open a model depends on the files published for it: GGUF for llama.cpp-based apps, MLX for Apple’s engine, the original weights for vLLM and SGLang. Compare every app.

Memory needed

Peak GPU memory at the native output size. Offloading moves the text encoder, or the whole pipeline, to system RAM between steps.

Precision Everything on GPU Text encoder offloaded Sequential offload Download
FP16 50.3 GB 40.8 GB 33.1 GB Original weights (opens in a new tab)
FP8 40.0 GB 35.2 GB 31.2 GB Original weights (opens in a new tab)

Components

Best hardware for CogVideoX 1.5 5B

The least expensive GPU in our catalog that runs it without offloading is the AMD Radeon PRO W7800 48GB (launch price $2,799) at FP8.

Quality Hardware Quant Memory Speed Runs
60Good quality (B) · 60 of 100: how capable the model is at FP16, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA RTX PRO 6000 Blackwell Workstation EditionNVIDIA RTX PRO 6000 Blackwell FP16 50.3 GB / 96.0 GB 11.0 min Runs well
60Good quality (B) · 60 of 100: how capable the model is at FP16, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H100 80GB SXMNVIDIA H100 80GB SXM FP16 50.3 GB / 80.0 GB 10.4 min Runs well
60Good quality (B) · 60 of 100: how capable the model is at FP16, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H800 80GB SXMNVIDIA H800 80GB SXM FP16 50.3 GB / 80.0 GB 10.4 min Runs well
60Good quality (B) · 60 of 100: how capable the model is at FP16, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GH200 Grace Hopper (96 GB GPU)NVIDIA GH200 Grace Hopper (96 GB GPU) FP16 50.3 GB / 96.0 GB 10.4 min Runs well
60Good quality (B) · 60 of 100: how capable the model is at FP16, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H100 NVLNVIDIA H100 NVL FP16 50.3 GB / 94.0 GB 11.3 min Runs well
60Good quality (B) · 60 of 100: how capable the model is at FP16, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA RTX PRO 6000 Blackwell Server EditionNVIDIA RTX PRO 6000 Blackwell Server Edition FP16 50.3 GB / 96.0 GB 11.3 min Runs well
58Good quality (B) · 58 of 100: how capable the model is at FP8, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H100 80GB PCIeNVIDIA H100 80GB PCIe FP8 40.0 GB / 80.0 GB 11.5 min Runs well
58Good quality (B) · 58 of 100: how capable the model is at FP8, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation EditionNVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition FP8 40.0 GB / 96.0 GB 10.9 min Runs well
60Good quality (B) · 60 of 100: how capable the model is at FP16, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H200 141GB SXMNVIDIA H200 141GB SXM FP16 50.3 GB / 141 GB 10.4 min Runs well
60Good quality (B) · 60 of 100: how capable the model is at FP16, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H200 NVLNVIDIA H200 NVL FP16 50.3 GB / 141 GB 11.3 min Runs well

Check it on your own hardware

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

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