gemma 3 12b it needs ~11.9 GB VRAM. RTX A4500 20GB has 20.0 GB. With Q4_K_M quantization, expect ~68 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
68.2 tok/s
TTFT
2839 ms
Safe context
108K
Memory
11.9 GB / 20.0 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 | 68.2 tok/s | 1548 ms | 108K |
| Coding | C | Runs well | 68.2 tok/s | 2839 ms | 108K |
| Agentic Coding | B | Runs well | 68.2 tok/s | 4129 ms | 108K |
| Reasoning | C | Runs well | 68.2 tok/s | 3355 ms | 108K |
| RAG | B | Runs well | 68.2 tok/s | 5162 ms | 108K |
How gemma 3 12b it (12B params) fits at each quantization level on RTX A4500 20GB (20.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.7 GB | Low | C47 |
Q3_K_S | 3 | 5.9 GB | Low | C48 |
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, RTX A4500 20GB can run gemma 3 12b it with a C grade (Runs well). Expected decode speed: 68.2 tok/s.
gemma 3 12b it (12B parameters) requires approximately 11.9 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 RTX A4500 20GB, gemma 3 12b it achieves approximately 68.2 tokens per second decode speed with a time-to-first-token of 2839ms using Q4_K_M quantization.
For coding workloads, gemma 3 12b it on RTX A4500 20GB receives a C grade with 68.2 tok/s and 108K context.
On RTX A4500 20GB, gemma 3 12b it can safely use up to 108K 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-rtx-a4500-20gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| Medium |
| C48 |
Q4_K_M | 4 | 7.3 GB | Medium | C49 |
Q5_K_M | 5 | 8.6 GB | High | C50 |
Q6_K | 6 | 9.8 GB | High | C51 |
Q8_0Best for your GPU | 8 | 12.8 GB | Very High | C50 |
F16 | 16 | 24.6 GB | Maximum | F0 |