~$1,999 MSRP
Can Gemma 3 4B run on Quadro RTX 6000 24GB?
YES — Runs Great
Gemma 3 4B needs ~8.1 GB VRAM. Quadro RTX 6000 24GB has 24.0 GB. With Q4_K_M quantization, expect ~56 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
Fit status
Runs well
Decode
56.0 tok/s
TTFT
3457 ms
Safe context
128K
Memory
8.1 GB / 24.0 GB
Memory breakdown
See how fast it feels
What limits this setup
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 56.0 tok/s | 1886 ms | 128K |
| Coding | B | Runs well | 56.0 tok/s | 3457 ms | 128K |
| Agentic Coding | A | Runs well | 56.0 tok/s | 5029 ms | 128K |
| Reasoning | B | Runs well | 56.0 tok/s | 4086 ms | 128K |
| RAG | A | Runs well | 56.0 tok/s | 6286 ms | 128K |
Quantization options
How Gemma 3 4B (4B params) fits at each quantization level on Quadro RTX 6000 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.6 GB | Low | B65 |
Q3_K_S | 3 | 2.0 GB | Low | B65 |
NVFP4 | 4 |
Get started
Copy-paste commands to run Gemma 3 4B on your machine.
Run
ollama run gemma3:4bUpgrade options
