Nemotron Mini 4B needs ~6.0 GB but RTX 3050 Ti Laptop 4GB only has 4.0 GB. Try a smaller quantization or lighter model.
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
2.0 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
21.1 tok/s
TTFT
9163 ms
Safe context
4K
Memory
6.0 GB / 4.0 GB
Offload
30%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 6.0 GB, but this setup only exposes 4.0 GB of usable VRAM.
Add more VRAM headroom
The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | F | Too heavy | 30.7 tok/s | 3437 ms | 4K |
| Coding | F | Too heavy | 21.1 tok/s | 9163 ms | 4K |
| Agentic Coding | F | Too heavy | 11.7 tok/s | 24136 ms | 4K |
| Reasoning | F | Too heavy | 21.1 tok/s | 10829 ms | 4K |
| RAG | F | Too heavy | 11.7 tok/s | 30170 ms | 4K |
How Nemotron Mini 4B (4B params) fits at each quantization level on RTX 3050 Ti Laptop 4GB (4.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_KBest for your GPU | 2 | 1.6 GB | Low | B56 |
Q3_K_S | 3 | 2.0 GB | Low | F0 |
NVFP4 | 4 | 2.2 GB | Medium | F0 |
Q4_K_M | 4 | 2.4 GB | Medium | F0 |
Q5_K_M | 5 | 2.9 GB | High | F0 |
Q6_K | 6 | 3.3 GB | High | F0 |
Q8_0 | 8 | 4.3 GB | Very High | F0 |
F16 | 16 | 8.2 GB | Maximum | F0 |
Upgrade-Optionen
GTX 1660 Super 6GBGünstige WahlMakes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
ca. $229 MSRP
RTX 3050 8GBBestes Preis-Leistungs-VerhältnisMakes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
ca. $249 MSRP
GTX 1060 6GBNVIDIA-UpgradeMakes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
ca. $249 MSRP
No, Nemotron Mini 4B requires more memory than RTX 3050 Ti Laptop 4GB provides.
Nemotron Mini 4B (4B parameters) requires approximately 6.0 GB of memory with Q4_K_M quantization.
The recommended quantization for Nemotron Mini 4B is Q4_K_M, which balances quality and memory efficiency.
On RTX 3050 Ti Laptop 4GB, Nemotron Mini 4B achieves approximately 21.1 tokens per second decode speed with a time-to-first-token of 9163ms using Q4_K_M quantization.
For coding workloads, Nemotron Mini 4B on RTX 3050 Ti Laptop 4GB receives a F grade with 21.1 tok/s and 4K context.
On RTX 3050 Ti Laptop 4GB, Nemotron Mini 4B can safely use up to 4K tokens of context. The model's official context limit is 4K, but available memory constrains the safe maximum.
Add more VRAM headroom. The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/nemotron-mini-4b-on-rtx-3050-ti-laptop-4gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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