Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored needs ~37.7 GB but RTX 4080 Super 16GB only has 16.0 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
21.7 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
3.1 tok/s
TTFT
61863 ms
Safe context
4K
Memory
37.7 GB / 16.0 GB
Offload
60%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 37.7 GB, but this setup only exposes 16.0 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 | 3.1 tok/s | 33743 ms | 4K |
| Coding | F | Too heavy | 3.1 tok/s | 61863 ms | 4K |
| Agentic Coding | F | Too heavy | 3.1 tok/s | 89982 ms | 4K |
| Reasoning | F | Too heavy | 3.1 tok/s | 73111 ms | 4K |
| RAG | F | Too heavy | 3.1 tok/s | 112478 ms | 4K |
How Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored (48B params) fits at each quantization level on RTX 4080 Super 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 18.7 GB | Low | F0 |
Q3_K_S | 3 | 23.5 GB | Low | F0 |
NVFP4 | 4 | 26.9 GB | Medium | F0 |
Q4_K_M | 4 | 29.3 GB | Medium | F0 |
Q5_K_M | 5 | 34.6 GB | High | F0 |
Q6_K | 6 | 39.4 GB | High | F0 |
Q8_0 | 8 | 51.4 GB | Very High | F0 |
F16 | 16 | 98.4 GB | Maximum | F0 |
アップグレードオプション
RTX A6000 48GBコスパ重視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.
〜$4,650 MSRP
RTX PRO 5000 Blackwell 48GBコスパ最良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.
〜$4,999 MSRP
Quadro RTX 8000 48GBNVIDIAアップグレード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.
〜$5,800 MSRP
No, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored requires more memory than RTX 4080 Super 16GB provides.
Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored (48B parameters) requires approximately 37.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored is Q4_K_M, which balances quality and memory efficiency.
On RTX 4080 Super 16GB, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored achieves approximately 3.1 tokens per second decode speed with a time-to-first-token of 61863ms using Q4_K_M quantization.
For coding workloads, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored on RTX 4080 Super 16GB receives a F grade with 3.1 tok/s and 4K context.
On RTX 4080 Super 16GB, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored can safely use up to 4K tokens of context. The model's official context limit is —, 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/hf-davidau--qwen3-48b-a4b-savant-commander-distill-12x-closed-open-heretic-uncensored-gguf-on-rtx-4080-super-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
