Can NVIDIA DGX Spark (GB10) · 64 GB run GLM-5.3-Flash (320B-A18B)?

Q: Can NVIDIA DGX Spark (GB10) · 64 GB run GLM-5.3-Flash (320B-A18B)?

No. It doesn't fit in memory. Rated by Local AI Advisor's engine at Q3_K_M.

64 GB unified · 273 GB/s memory bandwidth · GLM-5.3-Flash (320B-A18B) has 320B parameters (18B active per token).

Short answer

No. It doesn't fit in memory.

Needs ≈148 GB but only ≈57 GB is available after the OS, other apps and Open WebUI.

Why it doesn’t fit

Even its smallest practical version (Q3_K_M) needs about 148 GB for the model, its context memory and the runtime. After the operating system (≈3.2 GB), a browser with a few tabs (≈3.0 GB) and Open WebUI (≈1.0 GB), NVIDIA DGX Spark (GB10) · 64 GB has about 57 GB left, so it’s 91 GB short.

Ways to make it work

Close everything else
Not enough on its own: with every other app closed it’s still about 88 GB short.
Pick a smaller model from the same family
Get more memory
You’d want at least 155 GB of memory in total. The machines below are the cheapest that run it comfortably.
Check your exact setup
These pages assume typical settings. A shorter context or a lighter chat app can change the answer.
Check NVIDIA DGX Spark (GB10) · 64 GB

The same applies to every workload we rate (chat, coding questions, coding in a repository, agentic coding and long documents): they all need at least as much memory as chat.

Other models for NVIDIA DGX Spark (GB10) · 64 GB

The best-rated models for chat on this machine.

Everything NVIDIA DGX Spark (GB10) · 64 GB can run

Cheapest machines for GLM-5.3-Flash (320B-A18B)

Hardware rated comfortable or better for chat, lowest price first.

Same chip, other memory: 128 GB

Different tool, context size or workload?

These pages use typical settings. The full check models your exact setup.

Open sourceCheck my exact setup