# GLM-4-9B-0414: RAM and VRAM requirements

> GLM-4-9B-0414 is a 9B GLM model. At Q4_K_M it needs about **7.2 GB** to run and fits **33 of 40** tracked devices. Minimum to run: Nvidia GeForce RTX 3060 (12GB).

Last validated: 2026-08-03. Sources: Ollama, HuggingFace GGUF repos, vendor specs.

## Memory by quantization
| Quant | On disk | To run (4k context) |
| --- | --- | --- |
| Q4_K_M | 5.74 GB | ~7.2 GB |
| Q8_0 | 9.31 GB | ~10.8 GB |
| FP16 | 18.81 GB | ~20.3 GB |

Memory = weights + KV cache + ~0.8 GB runtime overhead, and varies ±15% with context length.

## Will it run on my device?
- **Apple M1 (8GB)** (8 GB): No, not enough memory
- **iPhone 17** (8 GB): No, not enough memory
- **iPhone 17 Pro** (12 GB): Yes, but tight
- **16GB RAM Laptop (CPU/iGPU only)** (16 GB): Yes, it runs (room for Q8_0)
- **Google Pixel 10 Pro** (16 GB): Yes, it runs
- **Nvidia GeForce RTX 3090 (24GB)** (24 GB): Yes, it runs (room for FP16)
- **Apple M4 Pro (48GB)** (48 GB): Yes, it runs (room for FP16)
- **Apple M3 Ultra (256GB)** (256 GB): Yes, it runs (room for FP16)

Full table of all 40 devices: https://localmodel.run/model/glm-4-9b-0414

## How to run
Use LM Studio (Mac/Windows) or Ollama / vLLM (Linux).

## Details
- Parameters: 9B
- Default context: 32k tokens
- License: MIT (commercial use: yes)
- Released: 2025-04
- HuggingFace: 32,072 downloads/mo, 109 likes

## FAQ
### How much VRAM or RAM does GLM-4-9B-0414 need?
About 7.2 GB at Q4_K_M (weights 5.74 GB + KV cache + overhead) at a 4k context. Budget ~10.8 GB for Q8_0.
### Can GLM-4-9B-0414 run on a laptop?
GLM-4-9B-0414 is large; you need a high-memory Mac or a 24 GB+ GPU at Q4_K_M.
### Can I use GLM-4-9B-0414 commercially?
Yes, MIT permits commercial use.

Sources: https://huggingface.co/THUDM/GLM-4-9B-0414, https://huggingface.co/zai-org/GLM-4-9B-0414, https://huggingface.co/bartowski/THUDM_GLM-4-9B-0414-GGUF, https://github.com/zai-org/GLM-4
More: https://localmodel.run/model/glm-4-9b-0414