Gemma 3 4B needs ~6.5 GB VRAM. RTX 3060 Ti 8GB has 8.0 GB. With Q4_K_M quantization, expect ~56 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
56.0 tok/s
TTFT
3457 ms
Safe context
27K
Memory
6.5 GB / 8.0 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 | 56.0 tok/s | 1886 ms | 27K |
| Coding | A | Runs well | 56.0 tok/s | 3457 ms | 27K |
| Agentic Coding | B | Runs with offload (needs ~0.2 GB host RAM) | 56.0 tok/s | 5029 ms | 27K |
| Reasoning | A | Runs well | 56.0 tok/s | 4086 ms | 27K |
| RAG | B | Runs with offload (needs ~0.2 GB host RAM) | 56.0 tok/s | 6286 ms |
How Gemma 3 4B (4B params) fits at each quantization level on RTX 3060 Ti 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.6 GB | Low | A72 |
Q3_K_S | 3 | 2.0 GB | Low | A73 |
NVFP4 | 4 |
Copy-paste commands to run Gemma 3 4B on your machine.
Run
ollama run gemma3:4bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3 8B | 8B | A | 38.6 tok/s | |
 Nemotron Nano 8B | 8B | A | 40.9 tok/s |
Yes, RTX 3060 Ti 8GB can run Gemma 3 4B with a A grade (Runs well). Expected decode speed: 56.0 tok/s.
Gemma 3 4B (4B parameters) requires approximately 6.5 GB of memory with Q4_K_M quantization.
The recommended quantization for Gemma 3 4B is Q4_K_M, which balances quality and memory efficiency.
On RTX 3060 Ti 8GB, Gemma 3 4B achieves approximately 56.0 tokens per second decode speed with a time-to-first-token of 3457ms using Q4_K_M quantization.
For coding workloads, Gemma 3 4B on RTX 3060 Ti 8GB receives a A grade with 56.0 tok/s and 27K context.
On RTX 3060 Ti 8GB, Gemma 3 4B can safely use up to 27K tokens of context. The model's official context limit is 128K, 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-3-4b-on-rtx-3060-ti-8gb" 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 |
| A73 |
Q4_K_M | 4 | 2.4 GB | Medium | A74 |
Q5_K_M | 5 | 2.9 GB | High | A75 |
Q6_K | 6 | 3.3 GB | High | A75 |
Q8_0Best for your GPU | 8 | 4.3 GB | Very High | A74 |
F16 | 16 | 8.2 GB | Maximum | F0 |
 InternVL2 8B | 8B | A | 40.9 tok/s |
 Ministral 3 8B | 8B | A | 38.6 tok/s |
 MiniCPM-V 2.6 8B | 8B | A | 40.9 tok/s |