Can I Run GLM-5 / GLM-5.1 on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
Written by Jakub Rusinowski · Last updated May 1, 2026
Yes — comfortably
Yes, comfortably — GLM-5.1 72B at Q3_K_M needs about 33.9 GB of the 128 GB usable on Framework Desktop (Ryzen AI Max+ 395, 128 GB), leaving ~94.1 GB spare and running at ~5.9 tok/s (estimated), with room for about 65,536 tokens of context.
Confidence: medium · Recommended quantization: Q3_K_M · Estimated speed: ~5.9 tok/s
Framework Desktop (Ryzen AI Max+ 395, 128 GB) — what it gives a model
| Usable memory for models | 128 GB |
| Memory bandwidth | 256 GB/s |
| Form factor | Mini PC |
| Operating system | Windows or Linux |
| Memory upgradeable | No — soldered |
GLM-5 / GLM-5.1 on Framework Desktop (Ryzen AI Max+ 395, 128 GB): memory by quantization
| Quant | Memory needed | Fits 128 GB? | Max context | Est. speed | Download |
|---|
| F16 | 147.2 GB | ✗ No | — | — | 144 GB |
| Q8_0 | 79.7 GB | ✓ Yes | 64K | ~2.5 tok/s | 76.5 GB |
| Q6_K | 62.3 GB | ✓ Yes | 64K | ~3.2 tok/s | 59 GB |
| Q5_K_M | 54.2 GB | ✓ Yes | 64K | ~3.6 tok/s | 51 GB |
| Q4_K_M | 46.7 GB | ✓ Yes | 64K | ~4.3 tok/s | 43.5 GB |
| Q3_K_M | 33.9 GB | ✓ Yes | 64K | ~5.9 tok/s | 30.7 GB |
| Q2_K | 26.9 GB | ✓ Yes | 64K | ~7.6 tok/s | 23.7 GB |
Which GLM-5 / GLM-5.1 sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|
| GLM-5 744B | 455.2 GB | ✗ Too large | — |
| GLM-5.1 72B | 46.7 GB | ✓ Fits | ~4.3 tok/s |
| GLM-5 32B | 22 GB | ✓ Fits | ~9.3 tok/s |
| GLM-5 9B | 7.4 GB | ✓ Fits | ~29.7 tok/s |
What to watch out for
- Q3_K_M is the only quantization that fits, and it is a heavily degraded one — expect noticeably worse output than the same model at Q4_K_M. A smaller model at Q4 is usually the better trade.
- 1 larger variant of GLM-5 / GLM-5.1 does not fit and would need CPU offload or different hardware.
- 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.
- Memory on this machine is not upgradeable, so the configuration you buy is the ceiling for every model you will ever run on it.
Framework Desktop 128 GB limitations
- Memory is soldered LPDDR5X — unusually for Framework, this is the one component that cannot be upgraded.
- ROCm/Vulkan support for Strix Halo is younger than CUDA; check your runtime supports it before buying.
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.
- 128 GB unified memory at 256 GB/s, shared between CPU and GPU.
- 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-5 / GLM-5.1 on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
Yes, comfortably — GLM-5.1 72B at Q3_K_M needs about 33.9 GB of the 128 GB usable on Framework Desktop (Ryzen AI Max+ 395, 128 GB), leaving ~94.1 GB spare and running at ~5.9 tok/s (estimated), with room for about 65,536 tokens of context.
Which quantization of GLM-5 / GLM-5.1 should I use on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
Q3_K_M — it needs about 33.9 GB of the 128 GB available, downloads as roughly 30.7 GB, and runs at an estimated 5.9 tokens/sec with up to 64K of context.
What limits GLM-5 / GLM-5.1 on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
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 Framework Desktop (Ryzen AI Max+ 395, 128 GB)
GLM-5 / GLM-5.1 on GPUs
What This Model Is Good At
Model & Tools
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