Can I Run GLM-4.7 / GLM-Z1 on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM)?
Written by Jakub Rusinowski · Last updated August 15, 2026
Yes, but it is tight
Yes, but it is tight — GLM-Z1 32B (Reasoning) at Q6_K needs about 28.9 GB of the 32 GB usable on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM), leaving only ~3.1 GB before the runtime starts swapping. Expect ~44.5 tok/s (estimated), with room for about 16,384 tokens of context.
Confidence: low · Recommended quantization: Q6_K · Estimated speed: ~44.5 tok/s
Get a personalized upgrade path →
As an Amazon Associate we earn from qualifying purchases. Cloud GPU links are referral links — we may earn a commission at no extra cost to you.
RTX 5090 Desktop (32 GB VRAM, 64 GB RAM) — what it gives a model
| Usable memory for models | 32 GB |
| Memory bandwidth | 1792 GB/s |
| Form factor | Desktop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
GLM-4.7 / GLM-Z1 on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM): memory by quantization
| Quant | Memory needed | Fits 32 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 66.6 GB | ✗ No | — | — | 64 GB |
| Q8_0 | 36.6 GB | ✗ No | — | — | 34 GB |
| Q6_K | 28.9 GB | ✓ Yes | 16K | ~44.5 tok/s | 26.2 GB |
| Q5_K_M | 25.3 GB | ✓ Yes | 32K | ~50.5 tok/s | 22.7 GB |
| Q4_K_M | 22 GB | ✓ Yes | 32K | ~57.8 tok/s | 19.3 GB |
| Q3_K_M | 16.3 GB | ✓ Yes | 64K | ~76.4 tok/s | 13.6 GB |
| Q2_K | 13.2 GB | ✓ Yes | 64K | ~92.9 tok/s | 10.5 GB |
Which GLM-4.7 / GLM-Z1 sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| GLM-Z1 32B (Reasoning) | 22 GB | ✓ Fits | ~57.8 tok/s |
| GLM-4.7-Flash 30B-A3B | 20.7 GB | ✓ Fits | ~235 tok/s |
| GLM-4 9B | 7.4 GB | ✓ Fits | ~148.4 tok/s |
What to watch out for
- This model does not publish its full attention configuration, so the KV-cache share of these figures is inferred from its parameter count rather than computed exactly.
RTX 5090 desktop limitations
- 575 W board power — budget for a 1000 W+ PSU and the heat it puts into the room.
- Models larger than 32 GB must offload to system RAM, which costs roughly an order of magnitude in speed.
Recommended setup
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 32 GB of VRAM on the NVIDIA GeForce RTX 5090 at 1792 GB/s.
- 64 GB of system RAM available for CPU offload when a model exceeds VRAM.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is inferred from the parameter count because this model does not publish its full attention configuration.
FAQ
Can I run GLM-4.7 / GLM-Z1 on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM)?
Yes, but it is tight — GLM-Z1 32B (Reasoning) at Q6_K needs about 28.9 GB of the 32 GB usable on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM), leaving only ~3.1 GB before the runtime starts swapping. Expect ~44.5 tok/s (estimated), with room for about 16,384 tokens of context.
Which quantization of GLM-4.7 / GLM-Z1 should I use on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM)?
Q6_K — it needs about 28.9 GB of the 32 GB available, downloads as roughly 26.2 GB, and runs at an estimated 44.5 tokens/sec with up to 16K of context.
What limits GLM-4.7 / GLM-Z1 on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Other Computers
Other Models on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM)
- GLM-5 / GLM-5.1 on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM)
- GLM-6 on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM)
- GPT-OSS on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM)
- Granite 3.0 on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM)
- IBM Granite 4.0 on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM)
GLM-4.7 / GLM-Z1 on GPUs
- GLM-4.7 / GLM-Z1 on NVIDIA GeForce RTX 5090
- GLM-4.7 / GLM-Z1 on NVIDIA GeForce RTX 5070
- GLM-4.7 / GLM-Z1 on NVIDIA GeForce RTX 5060 Ti 8GB
- GLM-4.7 / GLM-Z1 on NVIDIA GeForce RTX 5060
What This Model Is Good At
Model & Tools
← Can I Run It? | GLM-4.7 / GLM-Z1 model page | Check your hardware