GeForce RTX 4060 Ti 16 GB
NVIDIA
ExcellentRuns Phi-4 14B Q4_K_M entirely in memory
Model · Microsoft
At Q4_K_M with an 8K context, Phi-4 14B needs about 11.2 GB: a GPU with 12 GB or more runs it entirely in VRAM.
Official specData updated 24 days agoSource: Hugging Face config.json + model card
| Quantization | File size | Memory needed | Minimum GPU memory | Quality |
|---|---|---|---|---|
| BF16 | Not available | ~31.1 GB | 48 GB | Reference (unquantized) |
| Q8_0 | 14.5 GB | ~17.7 GB | 20 GB | Near-lossless |
| Q6_K | 11.2 GB | ~14.2 GB | 16 GB | Near-lossless |
| Q5_K_M | 9.9 GB | ~12.6 GB | 16 GB | Very good |
| Q4_K_MMost used | 8.4 GB | ~11.2 GB | 12 GB | Good — the usual choice |
| IQ4_XS | 7.4 GB | ~10.4 GB | 11 GB | Good — the usual choice |
| Q3_K_M | 6.9 GB | ~9.6 GB | 10 GB | Noticeable loss |
| Q2_K | 5.2 GB | ~8.1 GB | 10 GB | Significant loss |
File sizes: not available until imported from the model repository. Memory = weights (estimated from bits per weight) + KV cache + runtime overhead + safety margin. (BF16 ≈ 16 bpw, Q8_0 ≈ 8.5 bpw, Q6_K ≈ 6.57 bpw, Q5_K_M ≈ 5.7 bpw, Q4_K_M ≈ 4.9 bpw, IQ4_XS ≈ 4.46 bpw, Q3_K_M ≈ 4 bpw, Q2_K ≈ 3.17 bpw)
Q4, Q5 or Q8: how to choose a quantization
| RTX 509032 GB · 64 GB RAM~11.2 GB · 105–157 tok/s estimate | Excellent |
|---|---|
| RTX 409024 GB · 64 GB RAM~11.2 GB · 66–93 tok/s estimate | Excellent |
| RTX 309024 GB · 64 GB RAM~11.2 GB · 62–87 tok/s estimate | Excellent |
| RX 7900 XTX24 GB · 64 GB RAM~11.3 GB · 54–80 tok/s estimate | Excellent |
| RTX 5060 Ti 16 GB16 GB · 64 GB RAM~11.2 GB · 32–43 tok/s estimate | Excellent |
| RTX 5070 Ti16 GB · 64 GB RAM~11.2 GB · 60–84 tok/s estimate | Excellent |
| RTX 508016 GB · 64 GB RAM~11.2 GB · 64–89 tok/s estimate | Excellent |
| RTX 4060 Ti 16 GB16 GB · 64 GB RAM~11.2 GB · 21–28 tok/s estimate | Excellent |
| RTX 4070 Ti SUPER16 GB · 64 GB RAM~11.2 GB · 47–64 tok/s estimate | Excellent |
| RX 9070 XT16 GB · 64 GB RAM~11.3 GB · 39–56 tok/s estimate | Excellent |
| RTX 3060 12 GB12 GB · 64 GB RAM~11.2 GB · 26–35 tok/s estimate | Compatible with limits |
| RTX 407012 GB · 64 GB RAM~11.2 GB · 36–48 tok/s estimate | Compatible with limits |
| RTX 507012 GB · 64 GB RAM~11.2 GB · 47–64 tok/s estimate | Compatible with limits |
| RTX 40608 GB · 64 GB RAM~11.2 GB · 5–9.5 tok/s estimate | CPU/GPU offload |
| M3 Ultra (80-core GPU) · 512 GBMac Studio~11 GB · 45–76 tok/s estimate | Excellent |
|---|---|
| M4 Max (40-core GPU) · 128 GBMacBook Pro 14, MacBook Pro 16~11 GB · 32–51 tok/s estimate | Excellent |
| M3 Max (40-core GPU) · 128 GBMacBook Pro 14, MacBook Pro 16~11 GB · 24–37 tok/s estimate | Excellent |
| M4 Pro (20-core GPU) · 64 GBMac mini, MacBook Pro 14~11 GB · 17–25 tok/s estimate | Excellent |
| M4 Max (32-core GPU) · 36 GBMacBook Pro 14, MacBook Pro 16~11 GB · 25–38 tok/s estimate | Excellent |
| M5 · 32 GBMacBook Pro 14~11 GB · 10–15 tok/s estimate | Excellent |
| M4 · 32 GBMacBook Air, MacBook Pro 14~11 GB · 8–11 tok/s estimate | Compatible |
| M3 · 24 GBMacBook Air, MacBook Pro 14~11 GB · 6.5–9.5 tok/s estimate | Compatible |
EstimateData updated 24 days agoSource: Run LLM Locally engine
The KV cache grows with context: at 16K it adds about 3.1 GB on top of the weights.
With under 8 GB of VRAM, use a smaller quantization or a smaller model of the same family.
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NVIDIA
ExcellentRuns Phi-4 14B Q4_K_M entirely in memory
AMD
ExcellentRuns Phi-4 14B Q4_K_M entirely in memory
Apple Silicon
CompatibleRuns Phi-4 14B Q4_K_M entirely in memory
Unified memory PC
ExcellentRuns Phi-4 14B Q4_K_M entirely in memory
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