Can NVIDIA DGX Spark (GB10) · 64 GB run GLM-5.3 (753B-A40B)?
64 GB unified · 273 GB/s memory bandwidth · GLM-5.3 (753B-A40B) has 753B parameters (40B active per token).
Short answer
No. It doesn't fit in memory.
Needs ≈348 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 348 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 291 GB short.
Ways to make it work
Close everything else
Not enough on its own: with every other app closed it’s still about 288 GB short.
Pick a smaller model from the same family
Get more memory
You’d want at least 355 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.
- Qwen3.6 35B-A3B60–80 tok/sExcellent
- Qwen3-Next 80B-A3B Instruct80–110 tok/sExcellent
- Gemma 4 26B-A4B45–60 tok/sExcellent
- Qwen3.5 35B-A3B60–80 tok/sExcellent
- LFM2.5 24B-A2B120–160 tok/sExcellent
- gpt-oss-20b≈75 tok/sExcellent
Cheapest machines for GLM-5.3 (753B-A40B)
Hardware rated comfortable or better for chat, lowest price first.
- Mac Studio M5 Ultra 512 GB$7,099 · 16–25 tok/sComfortable
- Mac Studio M3 Ultra 512 GB$7,099 · 11–15 tok/sComfortable
Same chip, other memory: 128 GB
Different tool, context size or workload?
These pages use typical settings. The full check models your exact setup.