Can I Run GLM-5 / GLM-5.1 on MacBook Pro 16" (M4 Max, 128 GB)?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 1 maja 2026
No
No — GLM-5 / GLM-5.1 does not fit in MacBook Pro 16" (M4 Max, 128 GB). Even at Q2_K it needs about 250.6 GB against 96 GB usable, a shortfall of roughly 154.6 GB.
Confidence: medium
Get a personalized upgrade path →
Jako partner Amazon zarabiamy na kwalifikujących się zakupach. Linki do chmurowych GPU są linkami polecającymi — możemy otrzymać prowizję bez dodatkowych kosztów dla Ciebie.
MacBook Pro 16" (M4 Max, 128 GB) — what it gives a model
| Usable memory for models | 96 GB |
| Memory bandwidth | 546 GB/s |
| Form factor | Laptop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
GLM-5 / GLM-5.1 on MacBook Pro 16" (M4 Max, 128 GB): memory by quantization
| Quant | Memory needed | Fits 96 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.
MacBook Pro M4 Max 128 GB limitations
- Unified memory is soldered — the 128 GB decision is permanent and cannot be upgraded later.
- Sustained decode speed on battery is materially below the plugged-in figures quoted here.
Recommended setup
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
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 546 GB/s, shared between CPU and GPU.
- macOS reserves a share of unified memory for the system, so not all of it is available to a model.
- 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 MacBook Pro 16" (M4 Max, 128 GB)?
No — GLM-5 / GLM-5.1 does not fit in MacBook Pro 16" (M4 Max, 128 GB). Even at Q2_K it needs about 250.6 GB against 96 GB usable, a shortfall of roughly 154.6 GB.
What limits GLM-5 / GLM-5.1 on MacBook Pro 16" (M4 Max, 128 GB)?
Memory. MacBook Pro 16" (M4 Max, 128 GB) provides about 96 GB usable, and the smallest quantization of this model needs 250.6 GB.
Which runtime should I use?
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
Other Computers
- GLM-5 / GLM-5.1 on MacBook Pro M4 Max 48 GB
- GLM-5 / GLM-5.1 on MacBook Pro M4 Pro 24 GB
- GLM-5 / GLM-5.1 on MacBook Air M4 16 GB
Other Models on MacBook Pro 16" (M4 Max, 128 GB)
- GPT-OSS on MacBook Pro 16" (M4 Max, 128 GB)
- Granite 3.0 on MacBook Pro 16" (M4 Max, 128 GB)
- IBM Granite 4.0 on MacBook Pro 16" (M4 Max, 128 GB)
- IBM Granite 4.1 on MacBook Pro 16" (M4 Max, 128 GB)
- IBM Granite 4.2 on MacBook Pro 16" (M4 Max, 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