Home / Models / Phi-3 Medium 128K Instruct / NVIDIA RTX A6000 48 GB
Can Phi-3 Medium 128K Instruct run on NVIDIA RTX A6000 48 GB?
Yes. Calculated memory fit: Phi-3 Medium 128K Instruct can run entirely in this GPU’s usable VRAM at one or more supported quantizations.
Can it run?
- Can it run?
- Yes, full GPU fit (calculated estimate).
- Full GPU fit?
- Yes
- Model
- Phi-3 Medium 128K Instruct · 14B
- GPU
- NVIDIA RTX A6000 48 GB · 48 GB advertised
Memory calculation
Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.
| Model weights | 8.2 GB |
|---|---|
| KV cache | 1.6 GB |
| Runtime reserve | 0.9 GB |
| Safety margin | 0.5 GB |
| Required (estimated) | 11.2 GB |
| GPU usable VRAM | 43.2 GB |
Result: FITS IN VRAM
Quantization table
| Quantization | 2K | 4K | 8K | 16K | 32K | 64K | 128K |
|---|---|---|---|---|---|---|---|
| BF16 | Fits | Fits | Fits | Fits | Fits | Fits | Limited context |
| FP16 | Fits | Fits | Fits | Fits | Fits | Fits | Limited context |
| Q3 | Fits | Fits | Fits | Fits | Fits | Fits | Fits |
| Q4 | Fits | Fits | Fits | Fits | Fits | Fits | Fits |
| Q5 | Fits | Fits | Fits | Fits | Fits | Fits | Fits |
| Q6 | Fits | Fits | Fits | Fits | Fits | Fits | Fits |
| Q8 | Fits | Fits | Fits | Fits | Fits | Fits | Fits |
What fits entirely in VRAM?
- BF16 at 16K context
- BF16 at 2K context
- BF16 at 32K context
- BF16 at 4K context
- BF16 at 64K context
- BF16 at 8K context
- FP16 at 16K context
- FP16 at 2K context
- FP16 at 32K context
- FP16 at 4K context
- FP16 at 64K context
- FP16 at 8K context
What requires RAM offload?
Offload is shown only when the model does not fully fit in usable VRAM but stays within the modeled offload allowance.
Available graphics cards
These SKUs use this GPU chip. Amazon CTAs appear only for EXACT/HIGH matches. Absence of a price does not change the compatibility result above.
Lenovo 4X61L87571 graphics card NVIDIA RTX A6000 48 GB GDDR6
48 GB · Amazon unmatched
Sources
Model: official config microsoft/Phi-3-medium-128k-instruct (main). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: FITS_IN_VRAM. Amazon: affiliate commerce match, not a spec source.