Can I Run GLM-5 / GLM-5.1 on Apple M2 Pro?
Written by Jakub Rusinowski · Last updated September 29, 2026
Yes, but it's tight — GLM-5 32B at Q4_K_M needs 22 GB at 8K context (19.3 GB weights + 2.7 GB KV cache/overhead), leaving ~2 GB of the Apple M2 Pro's 24 GB usable memory, at ~5 tok/s (est.), with room for up to 16K context.
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Apple M2 Pro Specs
| VRAM | 32 GB unified memory |
| Memory Bandwidth | 200 GB/s |
GLM-5 32B on the Apple M2 Pro: VRAM by quantization
| Quant | VRAM needed | Fits 32 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 66.6 GB | ✗ No | — | — |
| Q8_0 | 36.6 GB | ✗ No | — | — |
| Q6_K | 28.9 GB | ✗ No | — | — |
| Q5_K_M | 25.3 GB | ✗ No | — | — |
| Q4_K_M | 22 GB | ✓ Yes | 16K | — |
| Q3_K_M | 16.3 GB | ✓ Yes | 32K | — |
| Q2_K | 13.2 GB | ✓ Yes | 32K | — |
Assumes an 8K-token context with an f16 KV cache, on an estimated architecture — this model publishes no config we can read. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 32 GB of unified memory. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the Apple M2 Pro: 8K 22 GB · 32K 27.5 GB ✗ · 125K 49 GB ✗. Past 32K it no longer fits 32 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? GLM-5 32B on 32 GB of system RAM, CPU only: runs comfortably.
GLM-5 / GLM-5.1 Sizes That Fit the Apple M2 Pro (at 8K context)
| GLM-5 32B | Q4_K_M · 22 GB at 8K context · ~5 tok/s (est.) |
| GLM-5 9B | Q4_K_M · 7.4 GB at 8K context · ~17 tok/s (est.) |
GLM-5 / GLM-5.1 needs ~22 GB but this GPU has 32 GB. Rent a RTX 4090 (24 GB)-class GPU by the hour instead of buying one:
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Can I run GLM-5 / GLM-5.1 on the Apple M2 Pro?
Yes, but it's tight — GLM-5 32B at Q4_K_M needs 22 GB at 8K context (19.3 GB weights + 2.7 GB KV cache/overhead), leaving ~2 GB of the Apple M2 Pro's 24 GB usable memory, at ~5 tok/s (est.), with room for up to 16K context.
What's the best GLM-5 / GLM-5.1 size for the Apple M2 Pro?
GLM-5 32B at Q4_K_M quantization needs 22 GB at 8K context (19.3 GB weights + 2.7 GB KV cache/overhead), estimated ~5 tokens/sec, up to 16K context.
GLM-5 / GLM-5.1 on Other GPUs
- GLM-5 / GLM-5.1 on NVIDIA GeForce RTX 5090
- GLM-5 / GLM-5.1 on Apple M4
- GLM-5 / GLM-5.1 on Apple M1 Pro
- GLM-5 / GLM-5.1 on Apple M5
- GLM-5 / GLM-5.1 on Apple M3 Pro
Popular Models on the Apple M2 Pro
VRAM Tier
Troubleshooting
- Ollama: "model requires more system memory than is available"
- Which GGUF quant should I download? (Q4 vs Q5 vs Q8)
Buying Guide
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