Makes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 933%.
~$1,499 MSRP
Granite 4.1 30B needs ~24.2 GB but RTX 5060 Ti 8GB only has 8.0 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
16.2 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
2.4 tok/s
TTFT
79102 ms
Safe context
4K
Memory
24.2 GB / 8.0 GB
Offload
70%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 24.2 GB, but this setup only exposes 8.0 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 | 2.4 tok/s | 43147 ms | 4K |
| Coding | F | Too heavy | 2.3 tok/s | 85035 ms | 4K |
| Agentic Coding | F | Too heavy | 2.4 tok/s | 115057 ms | 4K |
| Reasoning | F | Too heavy | 2.4 tok/s | 93484 ms | 4K |
| RAG | F | Too heavy | 2.4 tok/s | 143822 ms | 4K |
How Granite 4.1 30B (30B params) fits at each quantization level on RTX 5060 Ti 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.7 GB | Low | F0 |
Q3_K_S | 3 | 14.7 GB | Low | F0 |
NVFP4 | 4 |
Upgrade options
Makes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 933%.
~$1,499 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 1108%.
~$1,599 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 813%.
~$1,599 MSRP
Makes 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.
~$10,000 MSRP
No, Granite 4.1 30B requires more memory than RTX 5060 Ti 8GB provides.
Granite 4.1 30B (30B parameters) requires approximately 24.2 GB of memory with Q4_K_M quantization.
The recommended quantization for Granite 4.1 30B is Q4_K_M, which balances quality and memory efficiency.
On RTX 5060 Ti 8GB, Granite 4.1 30B achieves approximately 2.3 tokens per second decode speed with a time-to-first-token of 85035ms using Q4_K_M quantization.
For coding workloads, Granite 4.1 30B on RTX 5060 Ti 8GB receives a F grade with 2.3 tok/s and 4K context.
On RTX 5060 Ti 8GB, Granite 4.1 30B can safely use up to 4K 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/granite-4.1-30b-on-rtx-5060-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:
| Medium |
| F0 |
Q4_K_M | 4 | 18.3 GB | Medium | F0 |
Q5_K_M | 5 | 21.6 GB | High | F0 |
Q6_K | 6 | 24.6 GB | High | F0 |
Q8_0 | 8 | 32.1 GB | Very High | F0 |
F16 | 16 | 61.5 GB | Maximum | F0 |
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.