Gemma 3 27B needs ~32.6 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q4_K_M quantization, expect ~49 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
51.7 tok/s
TTFT
3741 ms
Safe context
27K
Memory
32.6 GB / 40.0 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 | S | Runs well | 51.7 tok/s | 2041 ms | 27K |
| Coding | S | Runs well | 49.3 tok/s | 3928 ms | 27K |
| Agentic Coding | A | Very compromised (needs ~1.4 GB host RAM) | 32.0 tok/s | 8796 ms | 27K |
| Reasoning | S | Runs well | 51.7 tok/s | 4421 ms | 27K |
| RAG | A | Very compromised (needs ~1.4 GB host RAM) | 32.0 tok/s | 10995 ms |
How Gemma 3 27B (27B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 10.5 GB | Low | A77 |
Q3_K_S | 3 | 13.2 GB | Low | A78 |
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 | 197.5 tok/s | ||
| 35B | S | 166 tok/s |
Yes, NVIDIA A100 40GB can run Gemma 3 27B with a S grade (Runs well). Expected decode speed: 49.3 tok/s.
Gemma 3 27B (27B parameters) requires approximately 32.6 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 A100 40GB, Gemma 3 27B achieves approximately 49.3 tokens per second decode speed with a time-to-first-token of 3928ms using Q4_K_M quantization.
For coding workloads, Gemma 3 27B on NVIDIA A100 40GB receives a S grade with 49.3 tok/s and 27K context.
On NVIDIA A100 40GB, Gemma 3 27B can safely use up to 27K 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-a100-40gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 27K |
| Medium |
| A79 |
Q4_K_M | 4 | 16.5 GB | Medium | A79 |
Q5_K_M | 5 | 19.4 GB | High | A80 |
Q6_K | 6 | 22.1 GB | High | A81 |
Q8_0Best for your GPU | 8 | 28.9 GB | Very High | A81 |
F16 | 16 | 55.4 GB | Maximum | F0 |
| 30B | S | 204.3 tok/s |
| 35B | S | 180.5 tok/s |
| 32B | S | 72.8 tok/s |