Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored needs ~48.6 GB VRAM. Gaudi 3 128GB has 128.0 GB. With Q4_K_M quantization, expect ~89 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
88.5 tok/s
TTFT
2189 ms
Safe context
242K
Memory
48.6 GB / 128.0 GB
The raw memory story may look fine, but the software ecosystem is still a constraint here.
Runtime ecosystem is narrower than CUDA
Intel GPUs can look attractive on memory per dollar, but local AI tooling, kernels, and model coverage are still broader and easier on CUDA today.
Prefer CUDA if you want the path of least resistance
If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 88.5 tok/s | 1194 ms | 242K |
| Coding | C | Runs well | 88.5 tok/s | 2189 ms | 242K |
| Agentic Coding | C | Runs well | 88.5 tok/s | 3183 ms | 242K |
| Reasoning | C | Runs well | 88.5 tok/s | 2587 ms | 242K |
| RAG | C | Runs well | 88.5 tok/s | 3979 ms | 242K |
How Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored (48B params) fits at each quantization level on Gaudi 3 128GB (128.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 18.7 GB | Low | D39 |
Q3_K_S | 3 | 23.5 GB | Low | D39 |
NVFP4 |
Copy-paste commands to run Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored on your machine.
Run
lms load hf-davidau--qwen3-48b-a4b-savant-commander-distill-12x-closed-open-heretic-uncensored-gguf && lms server startYes, Gaudi 3 128GB can run Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored with a C grade (Runs well). Expected decode speed: 88.5 tok/s.
Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored (48B parameters) requires approximately 48.6 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 Gaudi 3 128GB, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored achieves approximately 88.5 tokens per second decode speed with a time-to-first-token of 2189ms using Q4_K_M quantization.
For coding workloads, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored on Gaudi 3 128GB receives a C grade with 88.5 tok/s and 242K context.
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-gaudi-3-128gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 4 |
26.9 GB |
| Medium |
| D40 |
Q4_K_M | 4 | 29.3 GB | Medium | C40 |
Q5_K_M | 5 | 34.6 GB | High | C41 |
Q6_K | 6 | 39.4 GB | High | C42 |
Q8_0 | 8 | 51.4 GB | Very High | C44 |
F16Best for your GPU | 16 | 98.4 GB | Maximum | C48 |
On Gaudi 3 128GB, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored can safely use up to 242K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Prefer CUDA if you want the path of least resistance. If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.
Often yes, if your goal is the easiest setup and the widest runtime support. Intel can offer attractive memory capacity, but CUDA still tends to win on tooling maturity, guides, kernels, and model coverage for local AI.