Can I Run DeepSeek R1 Distill Llama 8B on a NVIDIA RTX 5060?
Runs comfortably at Q6_K — minimal quality loss.
3 quantizations fit your 8.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q6_KBEST | 7.6 GB | 9.1 GB | 6.6 GB | +0.4 GB |
| Q5_K_M | 6.7 GB | 8.2 GB | 5.7 GB | +1.3 GB |
| Q4_K_M | 5.8 GB | 7.3 GB | 4.8 GB | +2.2 GB |
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Top-ranked open-source models that fit in 8.0GB.
FAQ
Can the NVIDIA RTX 5060 run DeepSeek R1 Distill Llama 8B?
Yes. The NVIDIA RTX 5060's 8.0GB of VRAM is enough to run DeepSeek R1 Distill Llama 8B at Q6_K quantization (7.6GB required).
What's the best quantization to use?
Q6_K is the highest-precision quantization that fits in your 8.0GB. It uses about 7.6GB of memory and 9.1GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.