Text model · GLM
GL GLM-5.2: RAM and VRAM requirements
GLM-5.2 needs about 473.1 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~465.83 GB to download; KV cache and overhead add the rest), or about 808.7 GB at Q8_0. The lightest hardware that runs it is a high-memory machine.
GLM family · 744B params (Mixture-of-Experts: activates only 40B of 744B params per token, so generation is faster than the total size suggests) · released Jun 2026.
Shopping for hardware? See what runs GLM-5.2 →
Q4_K_M and Q8_0 are GGUF download (file) sizes. Memory @ Q4 includes the KV cache and overhead, so it runs larger than the file on disk.
Will it run on your device?
GLM-5.2 runs on 0 of 40 tracked devices at Q4_K_M.
Memory breakdown
How context length changes it
Longer context grows the KV cache, which for GLM-5.2 is sized by its 40B active params, not the full 744B. It needs ~473.1 GB at 4k and ~676.1 GB at 128k.
Quantization sizes
| Quantization | Size on disk |
|---|---|
| Q2_K | 311.6 GB est |
| Q3_K_M | 363.6 GB est |
| Q4_K_M (default) | 465.83 GB |
| Q5_K_M | 530.1 GB est |
| Q6_K | 610.1 GB est |
| Q8_0 | 801.36 GB |
| FP16 | 1507.99 GB |
Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.
Run it
llama-cli -hf unsloth/GLM-5.2-GGUF:Q4_K_M lms get unsloth/GLM-5.2-GGUF Which devices can run GLM-5.2?
Apple Silicon Macs
- Apple M1 (8GB) No
- Apple M2 (16GB) No
- Apple M4 (16GB) No
- Apple M5 (16GB) No
- Apple M3 Pro (18GB) No
- Apple M4 (24GB) No
- Apple M4 Pro (24GB) No
- Apple M5 (32GB) No
- Apple M4 Pro (48GB) No
- Apple M5 Pro (48GB) No
- Apple M4 Max (64GB) No
- Apple M4 Max (128GB) No
- Apple M5 Max (128GB) No
- Apple M3 Ultra (256GB) No
RAM-only laptops
iPhone & iPad
Android
NVIDIA GPUs
Same job, different size
Pick by what fits your memory: step down to free up VRAM, or step up if you have headroom.
Similar models
Head-to-head
FAQ
How much VRAM or RAM does GLM-5.2 need?
At Q4_K_M, GLM-5.2 needs about 473.1 GB (weights ~465.83 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~808.7 GB.
What is the Q4_K_M GGUF file size of GLM-5.2?
The Q4_K_M GGUF file is about 465.83 GB to download, and the Q8_0 GGUF is about 801.36 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~473.1 GB of memory at Q4_K_M.
Can GLM-5.2 run on a laptop?
GLM-5.2 is large; you need a high-memory Mac or multi-GPU setup at Q4_K_M.
Is GLM-5.2 cheaper to run because it is a MoE model?
It is faster, not lighter. GLM-5.2 activates only 40B of 744B params per token (so it runs quickly), but all experts must stay in memory, so it still needs memory for the full 744B.
Can I use GLM-5.2 commercially?
Yes. GLM-5.2 is licensed MIT, which permits commercial use.
Understand the numbers
Short guides to the ideas behind GLM-5.2's memory and quant figures.
Z.ai's flagship long-horizon model: 744B MoE, 40B active, DeepSeek Sparse Attention, 1M context, MIT. Quant sums from unsloth's split GGUFs (Q4_K_M and Q8_0 are UD dynamic quants). Even the 2-bit UD-Q2_K_XL is 254GB, beyond any single consumer machine; Ollama lists it as cloud-only. Multi-node or big-cluster territory.
Sources
Last validated 2026-08-03. Memory figures are estimates. See methodology.