Can Desktop PC · RTX PRO 6000 Blackwell · 128 GB RAM run GLM-5.3 (753B-A40B)?
96 GB VRAM + 128 GB RAM · 1792 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 ≈211 GB of VRAM + system RAM is available after the OS and other apps.
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 Windows (≈8.0 GB), a browser with a few tabs (≈3.0 GB) and Open WebUI (≈1.0 GB), Desktop PC · RTX PRO 6000 Blackwell · 128 GB RAM has about 211 GB left, so it’s 137 GB short.
Ways to make it work
Close everything else
Not enough on its own: with every other app closed it’s still about 134 GB short.
Pick a smaller model from the same family
Get more memory
You’d want at least 360 GB of VRAM plus RAM 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 Desktop PC · RTX PRO 6000 Blackwell · 128 GB RAM
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 Desktop PC · RTX PRO 6000 Blackwell · 128 GB RAM
The best-rated models for chat on this machine.
- Qwen3.6 35B-A3B260–360 tok/sExcellent
- Qwen3-Next 80B-A3B Instruct260–360 tok/sExcellent
- gpt-oss-120b≈180 tok/sExcellent
- Gemma 4 26B-A4B210–280 tok/sExcellent
- Qwen3.5 35B-A3B260–360 tok/sExcellent
- LFM2.5 24B-A2B530–720 tok/sExcellent
Cheapest machines for GLM-5.3 (753B-A40B)
Hardware rated comfortable or better for chat, lowest price first.
Different tool, context size or workload?
These pages use typical settings. The full check models your exact setup.