Can Qwen 3 32B run on RTX A5000 24GB?
BARELY — Tight on Memory
Qwen 3 32B needs ~26.7 GB VRAM. RTX A5000 24GB has 24.0 GB. With Q4_K_M quantization, expect ~17 tok/s.
Operating mode
Choose the run profile you care about
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
2.7 GB over capacity — needs offload or smaller quantization
Fit status
Very compromised (needs ~2 GB host RAM)
Decode
17.9 tok/s
TTFT
10809 ms
Safe context
5K
Memory
26.7 GB / 24.0 GB
Offload
10%
Memory breakdown
See how fast it feels
What limits this setup
It fits through host-memory offload, and offload is the main reason performance drops.
CPU or host-memory offload is active
About 10% of the working set spills out of accelerator memory, which usually hurts latency and sustained decode throughput.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Best improvement path
Remove offload with more accelerator memory
Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Increase host RAM if you keep offloading
This setup may need roughly {ram} GB of extra host RAM just for the offloaded portion, before OS and other tools.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs with offload | 19.3 tok/s | 5465 ms | 5K |
| Coding | A | Very compromised | 16.5 tok/s | 11755 ms | 5K |
| Agentic Coding | F | Too heavy | 12.4 tok/s | 22786 ms | 5K |
| Reasoning | A | Very compromised | 16.5 tok/s | 13892 ms | 5K |
| RAG | F | Too heavy | 12.4 tok/s | 28482 ms | 5K |
Quantization options
How Qwen 3 32B (32B params) fits at each quantization level on RTX A5000 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | S91 |
Q3_K_S | 3 | 15.7 GB | Low | S91 |
NVFP4Best for your GPU |
Get started
Copy-paste commands to run Qwen 3 32B on your machine.
Run
ollama run qwen3:32bYour hardware
