Home / Models / Phi-4 Mini Instruct / NVIDIA GTX 1660 6 GB
Can Phi-4 Mini Instruct run on NVIDIA GTX 1660 6 GB?
Yes. Calculated memory fit: Phi-4 Mini 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-4 Mini Instruct · 3.8B
- GPU
- NVIDIA GTX 1660 6 GB · 6 GB advertised
What else can NVIDIA GTX 1660 6 GB run? · Find other GPUs for Phi-4 Mini Instruct
Memory calculation
Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.
| Model weights | 2.3 GB |
|---|---|
| KV cache | 1.0 GB |
| Runtime reserve | 0.6 GB |
| Safety margin | 0.3 GB |
| Required (estimated) | 4.2 GB |
| GPU usable VRAM | 5.4 GB |
Result: FITS IN VRAM
Quantization table
| Quantization | 2K | 4K | 8K | 16K | 32K | 64K | 128K |
|---|---|---|---|---|---|---|---|
| BF16 | Offload | Offload | Offload | Offload | Offload | Offload | Offload |
| FP16 | Offload | Offload | Offload | Offload | Offload | Offload | Offload |
| Q3 | Fits | Fits | Fits | Fits | Limited context | Limited context | Limited context |
| Q4 | Fits | Fits | Fits | Fits | Limited context | Limited context | Limited context |
| Q5 | Fits | Fits | Fits | Limited context | Limited context | Limited context | Limited context |
| Q6 | Fits | Fits | Fits | Limited context | Limited context | Limited context | Limited context |
| Q8 | Offload | Offload | Offload | Offload | Offload | Offload | Offload |
What fits entirely in VRAM?
- Q3 at 16K context
- Q3 at 2K context
- Q3 at 4K context
- Q3 at 8K context
- Q4 at 16K context
- Q4 at 2K context
- Q4 at 4K context
- Q4 at 8K context
- Q5 at 2K context
- Q5 at 4K context
- Q5 at 8K context
- Q6 at 2K 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.
Performance
Separate from memory fit. Runtime is llama.cpp · quantization bucket Q4 (GGUF Q4_0 maps to Q4). Workload is llama-bench pp512 / tg128 (short context, batch 1, full GPU offload). This is not a ranking and not a 8K–128K speed claim.
- Model
- Phi-4 Mini Instruct
- GPU
- NVIDIA GTX 1660 6 GB
- Runtime
- llama.cpp · CUDA · model 1.0.0
- Decode
- ~65 tok/s · Calibrated estimate · MEDIUM confidence (spread ~58 tok/s–~73 tok/s)
- Prefill
- ~271 tok/s at a 512-token prompt · Calibrated estimate · MEDIUM confidence
- Time to first token
- ~1889 ms for a 512-token prompt (512 / prefill tok/s). Not estimated at 8K–128K.
decode_tps = GPU_efficiency × memory_bandwidth / model_weight_bytes; efficiency from same-gpu Llama 2 7B Q4_0 efficiency
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.
GIGABYTE GV-N1660OC-6GD graphics card NVIDIA GeForce GTX 1660 6 GB GDDR5
6 GB · Amazon EXACT
Check price on Amazon
MSI V379-013R graphics card NVIDIA GeForce GTX 1660 6 GB GDDR5
6 GB · Amazon unmatched
ASUS Phoenix PH-GTX1660-O6G NVIDIA GeForce GTX 1660 6 GB GDDR5
6 GB · Amazon unmatched
MSI V379-001R graphics card NVIDIA GeForce GTX 1660 6 GB GDDR5
6 GB · Amazon unmatched
ASUS TUF-GTX1660-O6G-GAMING NVIDIA GeForce GTX 1660 6 GB GDDR5
6 GB · Amazon unmatched
ASUS Dual -GTX1660-O6G EVO NVIDIA GeForce GTX 1660 6 GB GDDR5
6 GB · Amazon unmatched
ASUS Phoenix PH-GTX1660-6G NVIDIA GeForce GTX 1660 6 GB GDDR5
6 GB · Amazon unmatched
ASUS TUF Gaming TUF3-GTX1660-A6G-GAMING NVIDIA GeForce GTX 1660 6 GB GDDR5
6 GB · Amazon unmatched
MSI VENTUS GTX 1660 XS 6G OCV1 graphics card NVIDIA GeForce GTX 1660 6 GB GDDR5
6 GB · Amazon unmatched
ASUS Dual GTX1660-6G-EVO NVIDIA GeForce GTX 1660 6 GB GDDR5
6 GB · Amazon unmatched
ASUS TUF Gaming TUF3-GTX1660-O6G-GAMING NVIDIA GeForce GTX 1660 6 GB GDDR5
6 GB · Amazon unmatched
Sources
Model: official config microsoft/Phi-4-mini-instruct (main). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: CPU_RAM_OFFLOAD_REQUIRED. Amazon: affiliate commerce match, not a spec source.