Deploy GLM
Text & ChatGLM models from Zhipu AI are optimized for bilingual Chinese and English tasks. GLM-Z1 variants add deep reasoning capabilities, competing with DeepSeek R1 at up to 8x faster inference. All models use MIT license.
Deploy GLM in minutes
Starting at $0.53/hr on dedicated GPU
Available Variants (3)
| Model | GPU | VRAM | Price | Action |
|---|---|---|---|---|
GLM-4 9B 9B (Bilingual) | L4 | 24 GB | $0.53/hr | Deploy |
GLM-Z1 9B 9B (Reasoning) | L4 | 24 GB | $0.53/hr | Deploy |
GLM-Z1 32B 32B (Deep Reasoning) | RTX A6000 | 48 GB | $0.66/hr | Deploy |
Prices include the service fee. Charges follow actual running time.
Requirements
ModelPilot assigns 24–48GB cloud GPUs across the listed variants. Actual local VRAM requirements vary with model variant, precision, quantization, resolution, and workflow settings.
On ModelPilot, deploy on a dedicated cloud GPU (up to 80GB VRAM) starting at $0.53/hr with no setup required.
Use Cases
- ✓Chinese-English bilingual AI
- ✓Bilingual customer support
- ✓Chinese content generation
- ✓Fast reasoning tasks
Related Models
Frequently Asked Questions
How much GPU memory is allocated for GLM?
The listed ModelPilot variants use 24–48GB cloud GPUs. Local memory needs vary with the variant, precision, quantization, and workflow settings.
How much does it cost to run GLM?
Starting at $0.53/hr on a dedicated GPU. Charges are calculated from actual running time, with auto-stop when credits run out.
How long does GLM take to deploy?
Text models typically deploy in 5–15 minutes including model download.
Can I run GLM on my local GPU?
It depends on the selected variant, precision, quantization, and workflow settings. Compare the variants below with your available VRAM; the table shows ModelPilot's cloud GPU allocation, not a universal local minimum.
Ready to deploy GLM?
Pick your GPU and have it running in minutes. No infrastructure setup required.