Gemma 2 27B needs ~33.7 GB VRAM. Quadro RTX 8000 48GB has 48.0 GB. With Q4_K_M quantization, expect ~30 tok/s.
Operating mode
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
29.6 tok/s
TTFT
6549 ms
Safe context
8K
Memory
33.7 GB / 48.0 GB
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.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 29.6 tok/s | 3572 ms | 8K |
| Coding | A | Runs well | 29.6 tok/s | 6549 ms | 8K |
| Agentic Coding | B | Tight fit | 29.6 tok/s | 9526 ms | 8K |
| Reasoning | A | Runs well | 29.6 tok/s | 7740 ms | 8K |
| RAG | B | Tight fit | 29.6 tok/s | 11908 ms | 8K |
How Gemma 2 27B (27B params) fits at each quantization level on Quadro RTX 8000 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 10.5 GB | Low | B63 |
Q3_K_S | 3 | 13.2 GB | Low | B64 |
NVFP4 | 4 | 15.1 GB | Medium | B64 |
Q4_K_M | 4 | 16.5 GB | Medium | B65 |
Q5_K_M | 5 | 19.4 GB | High | B66 |
Q6_K | 6 | 22.1 GB | High | B66 |
Q8_0Best for your GPU | 8 | 28.9 GB | Very High | B68 |
F16 | 16 | 55.4 GB | Maximum | F0 |
Copy-paste commands to run Gemma 2 27B on your machine.
Run
ollama run gemma2:27bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 70.1 tok/s | ||
| 35B | S | 58.9 tok/s | ||
| 30B | S | 72.5 tok/s | ||
| 35B | S | 64.1 tok/s | ||
| 32B | S | 25.8 tok/s |
Yes, Quadro RTX 8000 48GB can run Gemma 2 27B with a A grade (Runs well). Expected decode speed: 29.6 tok/s.
Gemma 2 27B (27B parameters) requires approximately 33.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Gemma 2 27B is Q4_K_M, which balances quality and memory efficiency.
On Quadro RTX 8000 48GB, Gemma 2 27B achieves approximately 29.6 tokens per second decode speed with a time-to-first-token of 6549ms using Q4_K_M quantization.
For coding workloads, Gemma 2 27B on Quadro RTX 8000 48GB receives a A grade with 29.6 tok/s and 8K context.
On Quadro RTX 8000 48GB, Gemma 2 27B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/gemma-2-27b-on-quadro-rtx-8000-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: