What hardware runs GLM 4.5 Air?
GLM 4.5 Air is a 110.47B-parameter mixture-of-experts model with 14.96B active parameters (mit license). The community's favorite big MoE: agentic coding chops and genuinely good prose in one 12B-active package.
All figures assume an f16 KV cache, a 0.6 GB display reserve on the GPU, and 64 GB of DDR5 system RAM for the offload tiers. Tune these in the calculator.
Minimum VRAM by quant and context
| Quant | File size | 8K | 16K | 32K | 64K | 128K |
|---|---|---|---|---|---|---|
| Q2_K * | 42.2 GB | 45.5 GB | 47 GB | 50 GB | 56 GB | 68 GB |
| Q3_K_M | 53.3 GB | 56.6 GB | 58.1 GB | 61.1 GB | 67.1 GB | 79.1 GB |
| Q4_K_M | 68.0 GB | 71.3 GB | 72.8 GB | 75.8 GB | 81.8 GB | 93.8 GB |
| Q5_K_M | 77.8 GB | 81.1 GB | 82.6 GB | 85.6 GB | 91.6 GB | 103.6 GB |
| Q6_K | 92.2 GB | 95.5 GB | 97 GB | 100 GB | 106 GB | 118 GB |
| Q8_0 | 109.4 GB | 112.7 GB | 114.2 GB | 117.2 GB | 123.2 GB | 135.2 GB |
| IQ4_XS | 56.3 GB | 59.6 GB | 61.1 GB | 64.1 GB | 70.1 GB | 82.1 GB |
Full-GPU figures: weights + f16 KV cache + overhead. * below our recommended floor of Q3_K_M.
GPU compatibility
| GPU | 8K | 16K | 32K | 64K | 128K |
|---|---|---|---|---|---|
| NVIDIA GeForce RTX 5090 | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS |
| NVIDIA GeForce RTX 5080 | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| NVIDIA GeForce RTX 5070 Ti | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| NVIDIA GeForce RTX 5070 | IQ4_XS | IQ4_XS | Q3_K_M | — | — |
| NVIDIA GeForce RTX 5060 Ti 16GB | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| NVIDIA GeForce RTX 5060 | IQ4_XS | IQ4_XS | — | — | — |
| NVIDIA GeForce RTX 4090 | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| NVIDIA GeForce RTX 4080 SUPER | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| NVIDIA GeForce RTX 4070 Ti SUPER | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| NVIDIA GeForce RTX 4070 | IQ4_XS | IQ4_XS | Q3_K_M | — | — |
| NVIDIA GeForce RTX 4060 Ti 16GB | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| NVIDIA GeForce RTX 4060 | IQ4_XS | IQ4_XS | — | — | — |
| NVIDIA GeForce RTX 3090 | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| NVIDIA GeForce RTX 3080 10GB | IQ4_XS | IQ4_XS | IQ4_XS | — | — |
| NVIDIA GeForce RTX 3070 | IQ4_XS | IQ4_XS | — | — | — |
| NVIDIA GeForce RTX 3060 Ti | IQ4_XS | IQ4_XS | — | — | — |
| NVIDIA GeForce RTX 3060 12GB | IQ4_XS | IQ4_XS | Q3_K_M | — | — |
| NVIDIA GeForce RTX 2080 Ti | IQ4_XS | IQ4_XS | IQ4_XS | — | — |
| NVIDIA GeForce GTX 1080 Ti | IQ4_XS | IQ4_XS | IQ4_XS | — | — |
| AMD Radeon RX 9070 XT | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| AMD Radeon RX 7900 XTX | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| AMD Radeon RX 7900 XT | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| AMD Radeon RX 7800 XT | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| AMD Radeon RX 7600 XT | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| AMD Radeon RX 6800 XT | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| AMD Radeon RX 6700 XT | IQ4_XS | IQ4_XS | Q3_K_M | — | — |
| Intel Arc B580 | IQ4_XS | IQ4_XS | Q3_K_M | — | — |
| Intel Arc A770 16GB | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| Apple M2 (16GB) | IQ4_XS | IQ4_XS | Q3_K_M | — | — |
| Apple M2 Pro (32GB) | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | — |
| Apple M2 Max (64GB) | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS |
| Apple M2 Ultra (128GB) | Q6_K | Q5_K_M | Q5_K_M | Q5_K_M | Q4_K_M |
| Apple M3 (16GB) | IQ4_XS | IQ4_XS | Q3_K_M | — | — |
| Apple M3 Pro (36GB) | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS |
| Apple M3 Max (64GB) | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS |
| Apple M3 Ultra (96GB) | Q4_K_M | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS |
| Apple M4 (16GB) | IQ4_XS | IQ4_XS | Q3_K_M | — | — |
| Apple M4 Pro (48GB) | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS |
| Apple M4 Max (64GB) | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS | IQ4_XS |
| CPU only / integrated graphics | — | — | — | — | — |
Fits on GPUExpert offloadPartial offloadCPU only
Quant guidance
Our floor for GLM 4.5 Air is Q3_K_M — below that, quality degrades faster than the VRAM savings are worth (large models tolerate low bpw better than small ones, which is why the floor is lower here). Prefer the highest quant that still lands "Fits on GPU" or “Expert offload” at your context length in the table above.
Recommended run command
Q3_K_M at 32K on a NVIDIA GeForce RTX 5070-class GPU (Expert offload):
llama-server -m GLM-4.5-Air-Q3_K_M.gguf -c 32768 --flash-attn -ngl 99 --n-cpu-moe 46
Frequently asked questions
How much VRAM does GLM 4.5 Air need?
At Q3_K_M and 32K context, GLM 4.5 Air needs about 61.1 GB of VRAM to run fully on GPU (weights + KV cache + overhead). As a mixture-of-experts model it can also run with far less VRAM via expert offload, keeping experts in system RAM.
What is the smallest GPU that can run GLM 4.5 Air?
The NVIDIA GeForce RTX 5070 (12 GB) is the smallest GPU in our set that runs GLM 4.5 Air well at 32K context, using expert offload with 64 GB of system RAM.
What quantization should I use for GLM 4.5 Air?
We recommend Q3_K_M or higher. Q4_K_M weighs 68.0 GB (5.28 bits/weight); going below Q3_K_M costs noticeable quality on a model this size.
How long a context can GLM 4.5 Air handle?
GLM 4.5 Air supports up to 128K tokens. KV cache grows linearly with context.
Can I run GLM 4.5 Air without a GPU?
Not realistically — even at 8K context the weights don't fit in 64 GB of system RAM.