Can You Run GLM-5.3 (753B MoE)? VRAM Requirements
GLM-5.3 (753B MoE) has 753B total parameters (MoE, 40B active per token). Running it at Q4_K_M (GGUF) with 16K context takes roughly 463 GB of memory (428 GB weights + 1.4 GB KV cache + runtime overhead). The minimum viable hardware is about Mac M3 Ultra 512GB. All numbers are planning estimates, verified 2026-09-05.
⚠ Some architecture details of this model are estimated — treat results as ballpark figures.
VRAM by quantization (16K context)
| Quantization | Weights | Total needed | Minimum hardware |
|---|---|---|---|
| FP16 / BF16 | 1.37 TB | 1.48 TB | 9× B200 192GB |
| FP8 | 701 GB | 759 GB | 5× B200 192GB |
| Q8_0 (GGUF) | 743 GB | 804 GB | 5× B200 192GB |
| Q6_K (GGUF) | 575 GB | 622 GB | 4× B200 192GB |
| Q5_K_M (GGUF) | 498 GB | 539 GB | 8× H100 80GB |
| MXFP4 | 372 GB | 403 GB | Mac M3 Ultra 512GB |
| NVFP4 | 372 GB | 403 GB | Mac M3 Ultra 512GB |
| Q4_K_M (GGUF)recommended | 428 GB | 463 GB | Mac M3 Ultra 512GB |
| Q3_K_M (GGUF) | 330 GB | 357 GB | Mac M3 Ultra 512GB |
| Q2_K (GGUF) | 245 GB | 266 GB | Mac M3 Ultra 512GB |
How context length changes memory (Q4_K_M (GGUF))
| Context | KV cache | Total needed |
|---|---|---|
| 4K | 0.3 GB | 462 GB |
| 16K | 1.4 GB | 463 GB |
| 64K | 5.5 GB | 467 GB |
| 128K | 11.0 GB | 473 GB |
| 256K | 21.9 GB | 484 GB |
| 1M | 83.7 GB | 546 GB |
KV cache grows linearly with context; FP8 KV cache halves it again (try it in the calculator below).
Customize the estimate
LLM VRAM Calculator — Can I Run It?
Estimate how much GPU memory (VRAM) you need to run open-weight LLMs like Kimi K3, DeepSeek R1, Qwen3, or Llama locally. Pick a model, quantization, and context length — the calculator adds up weights, KV cache, and runtime overhead, then shows which GPUs or Macs can fit it. Runs entirely in your browser: no upload, no signup.
753B total params · 40B active (MoE) · max 1M context · specs partially estimated
Recommended balance · ~0.61 bytes/param
Estimated memory needed
473 GB
Architecture details for this model are estimated — treat results as a ballpark.
Will it fit?
Assumes ~92% of device memory is usable. Multi-GPU counts are for tensor/pipeline parallel serving (vLLM, SGLang); Apple Silicon uses unified memory via llama.cpp or MLX.
FAQ
How much VRAM does GLM-5.3 (753B MoE) need?
About 463 GB at the recommended Q4_K_M (GGUF) quantization with 16K context: 428 GB for weights, 1.4 GB for KV cache, plus runtime overhead. Longer context grows the KV cache.
What is the minimum hardware for GLM-5.3 (753B MoE)?
Roughly Mac M3 Ultra 512GB, assuming 92% of device memory is usable. Lower-end setups can try more aggressive quantization (Q3/Q2) at a noticeable quality cost.
Can I run GLM-5.3 (753B MoE) on a Mac?
Yes. At Q4_K_M (GGUF) with 16K context it needs about 463 GB, which fits the unified memory of a Mac M3 Ultra 512GB via llama.cpp or MLX.
Which quantization should I use for GLM-5.3 (753B MoE)?
Q4_K_M is the recommended balance of size and quality; with headroom, Q6_K or Q8_0 reduce quality loss further.