Can I Run GLM-5 / GLM-5.1 on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 1 maja 2026
No
No — GLM-5 / GLM-5.1 does not fit in Framework Desktop (Ryzen AI Max+ 395, 128 GB). Even at Q2_K it needs about 250.6 GB against 128 GB usable, a shortfall of roughly 122.6 GB.
Confidence: medium
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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 | 1494 GB | ✗ No | — | — | 1488 GB |
| Q8_0 | 796.5 GB | ✗ No | — | — | 790.5 GB |
| Q6_K | 616.1 GB | ✗ No | — | — | 610.1 GB |
| Q5_K_M | 533.3 GB | ✗ No | — | — | 527.3 GB |
| Q4_K_M | 455.2 GB | ✗ No | — | — | 449.2 GB |
| Q3_K_M | 323.2 GB | ✗ No | — | — | 317.1 GB |
| Q2_K | 250.6 GB | ✗ No | — | — | 244.6 GB |
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.
- 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)?
No — GLM-5 / GLM-5.1 does not fit in Framework Desktop (Ryzen AI Max+ 395, 128 GB). Even at Q2_K it needs about 250.6 GB against 128 GB usable, a shortfall of roughly 122.6 GB.
What limits GLM-5 / GLM-5.1 on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
Memory. Framework Desktop (Ryzen AI Max+ 395, 128 GB) provides about 128 GB usable, and the smallest quantization of this model needs 250.6 GB.
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-5.3-Flash on Framework Desktop (Ryzen AI Max+ 395, 128 GB)
- GPT-OSS on Framework Desktop (Ryzen AI Max+ 395, 128 GB)
- Granite 3.0 on Framework Desktop (Ryzen AI Max+ 395, 128 GB)
- IBM Granite 4.0 on Framework Desktop (Ryzen AI Max+ 395, 128 GB)
- IBM Granite 4.1 on Framework Desktop (Ryzen AI Max+ 395, 128 GB)
GLM-5 / GLM-5.1 on GPUs
- GLM-5 / GLM-5.1 on NVIDIA GeForce RTX 5090
- GLM-5 / GLM-5.1 on NVIDIA GeForce RTX 5070
- GLM-5 / GLM-5.1 on NVIDIA GeForce RTX 5060 Ti 8GB
- GLM-5 / GLM-5.1 on NVIDIA GeForce RTX 5060
What This Model Is Good At
- Best local LLMs for coding
- Best local LLMs for document analysis
- Best local LLMs for enterprise assistant
Model & Tools
← Can I Run It? | GLM-5 / GLM-5.1 model page | Check your hardware