gemma 3 12b it needs ~14.7 GB VRAM. NVIDIA A40 48GB has 48.0 GB. With Q4_K_M quantization, expect ~74 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
74.2 tok/s
TTFT
2610 ms
Safe context
395K
Memory
14.7 GB / 48.0 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 | C | Runs well | 74.2 tok/s | 1424 ms | 395K |
| Coding | C | Runs well | 74.2 tok/s | 2610 ms | 395K |
| Agentic Coding | C | Runs well | 74.2 tok/s | 3797 ms | 395K |
| Reasoning | C | Runs well | 74.2 tok/s | 3085 ms | 395K |
| RAG | C | Runs well | 74.2 tok/s | 4746 ms | 395K |
How gemma 3 12b it (12B params) fits at each quantization level on NVIDIA A40 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.7 GB | Low | C42 |
Q3_K_S | 3 | 5.9 GB | Low | C42 |
NVFP4 | 4 |
Copy-paste commands to run gemma 3 12b it on your machine.
Run
lms load hf-maziyarpanahi--gemma-3-12b-it-gguf && lms server startYes, NVIDIA A40 48GB can run gemma 3 12b it with a C grade (Runs well). Expected decode speed: 74.2 tok/s.
gemma 3 12b it (12B parameters) requires approximately 14.7 GB of memory with Q4_K_M quantization.
The recommended quantization for gemma 3 12b it is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA A40 48GB, gemma 3 12b it achieves approximately 74.2 tokens per second decode speed with a time-to-first-token of 2610ms using Q4_K_M quantization.
For coding workloads, gemma 3 12b it on NVIDIA A40 48GB receives a C grade with 74.2 tok/s and 395K context.
On NVIDIA A40 48GB, gemma 3 12b it can safely use up to 395K tokens of context. The model's official context limit is —, 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/hf-maziyarpanahi--gemma-3-12b-it-gguf-on-a40-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
6.7 GB |
| Medium |
| C42 |
Q4_K_M | 4 | 7.3 GB | Medium | C42 |
Q5_K_M | 5 | 8.6 GB | High | C43 |
Q6_K | 6 | 9.8 GB | High | C43 |
Q8_0 | 8 | 12.8 GB | Very High | C44 |
F16Best for your GPU | 16 | 24.6 GB | Maximum | C48 |