Can I run GLM-4.5-Air?

GLM-4.5-Air needs about 78.0 GB of memory at Q4_K_M, and the cheapest GPU we track that holds it is the NVIDIA RTX Pro 6000 Blackwell 96GB (96 GB, $8565 list price). 7 of the 82 devices we track run it fully at Q4. These are estimates, not measured benchmarks.

110.5B parameters, by zai-org. License: mit. Model card (params from HF API, retrieved 2026-10-28) · How much VRAM for 120B models · Best GPU for GLM · Q4 vs Q8 vs FP16 · MoE: 12.0B active per token

Q4_K_M needs

78.0 GB 67.0 GB weights

Q8_0 needs

136.0 GB 117.4 GB weights

FP16 needs

255.1 GB 220.9 GB weights

7 of 82 tracked GPUs and Macs run it fully at Q4.

Memory by context length

Longer chats and documents need more memory for the KV cache. All 46 layers keep a full cache. Sizes assume an FP16 KV cache; a Q8 cache roughly halves the cache part.

From the model's config.json (46 full-attention layers × 8 KV heads × 128 head size, retrieved 2026-10-28). Check the model card for its maximum supported context. Try other sizes in the VRAM calculator or compare models in our context length guide.

Can I run GLM-4.5-Air on a specific GPU or Mac?

Direct yes-or-no checks for popular hardware, with the quant that fits and an estimated tokens/sec range.

• Can I run GLM-4.5-Air on an RTX 4090?Q4Won’t fit
• Can I run GLM-4.5-Air on an RTX 5090?Q4Won’t fit
• Can I run GLM-4.5-Air on dual RTX 3090s?Q4Won’t fit
• Can I run GLM-4.5-Air on a Mac mini 64GB?Q4Won’t fit
• Can I run GLM-4.5-Air on a Mac Studio 256GB?Q8Fits
• Can I run GLM-4.5-Air on an RTX 3090?Q4Won’t fit

Which hardware runs it

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