Gemma 3 27B needs ~35.3 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~28 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
29.8 tok/s
TTFT
6489 ms
Safe context
57K
Memory
35.3 GB / 64.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 29.8 tok/s | 3539 ms | 57K |
| Coding | A | Runs well | 28.4 tok/s | 6813 ms | 57K |
| Agentic Coding | S | Runs well | 29.8 tok/s | 9438 ms | 57K |
| Reasoning | A | Runs well | 29.8 tok/s | 7669 ms | 57K |
| RAG | S | Runs well | 29.8 tok/s | 11798 ms | 57K |
How Gemma 3 27B (27B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 10.5 GB | Low | A74 |
Q3_K_S | 3 | 13.2 GB | Low | A74 |
NVFP4 | 4 |
Copy-paste commands to run Gemma 3 27B on your machine.
Run
ollama run gemma3Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 70.8 tok/s | ||
| 35B | S | 59.5 tok/s |
Yes, NVIDIA A16 64GB can run Gemma 3 27B with a A grade (Runs well). Expected decode speed: 28.4 tok/s.
Gemma 3 27B (27B parameters) requires approximately 35.3 GB of memory with Q4_K_M quantization.
The recommended quantization for Gemma 3 27B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA A16 64GB, Gemma 3 27B achieves approximately 28.4 tokens per second decode speed with a time-to-first-token of 6813ms using Q4_K_M quantization.
For coding workloads, Gemma 3 27B on NVIDIA A16 64GB receives a A grade with 28.4 tok/s and 57K context.
On NVIDIA A16 64GB, Gemma 3 27B can safely use up to 57K tokens of context. The model's official context limit is 131K, 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-3-27b-on-a16-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| Medium |
| A75 |
Q4_K_M | 4 | 16.5 GB | Medium | A75 |
Q5_K_M | 5 | 19.4 GB | High | A76 |
Q6_K | 6 | 22.1 GB | High | A76 |
Q8_0Best for your GPU | 8 | 28.9 GB | Very High | A78 |
F16 | 16 | 55.4 GB | Maximum | F0 |
| 30B | S | 73.2 tok/s |
| 35B | S | 64.7 tok/s |
| 32B | S | 26.1 tok/s |