Can the RTX 5060 run Llama 3.1 8B?
Just. Llama 3.1 8B at Q4_K_M needs about 7.3 GB of the RTX 5060's 8 GB, running at an estimated 47 tok/s. Keep context short and close other GPU apps.
Every quantization
Llama 3.1 8B (8B) on 8 GB
| Quant | Weights | Needs | Fit | Est. speed |
|---|---|---|---|---|
| Q4_K_M | 5.5 GB | 7.3 GB | Tight | ~47 tok/s |
| Q5_K_M | 7 GB | 8.8 GB | Too big | - |
| Q8_0 | 10 GB | 11.8 GB | Too big | - |
| FP16 | 16 GB | 17.8 GB | Too big | - |
Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the RTX 5060's 448 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.
Run it
Copy, paste, go
ollama run llama3.1:8bllama-server -hf bartowski/Meta-Llama-3.1-8B-Instruct-GGUF -ngl 99Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Llama 3.1 8B details →
Compare
Same model, other hardware - and other models on this card
Llama 3.1 8B on other hardware
- RTX 5090~187 tok/s
- RTX 5090 D~187 tok/s
- RTX 6000D~164 tok/s
- RTX 4090~114 tok/s
- RTX 3090~100 tok/s
- Radeon RX 7900 XTX~100 tok/s
- RTX 5080~100 tok/s
- RTX 3080 Ti~95 tok/s
Also runs on the RTX 5060
- Mistral-7B-Instruct-v0.2~64 tok/s
- Qwen3.5 4B~86 tok/s
- Qwen3-4B-Instruct-2507~128 tok/s
- NVIDIA Nemotron 3 Nano 4B~128 tok/s
- Phi-4 Mini~103 tok/s
Frequently asked
Quick answers
Can the NVIDIA RTX 5060 run Llama 3.1 8B?
Just. Llama 3.1 8B at Q4_K_M needs about 7.3 GB of the RTX 5060's 8 GB, running at an estimated 47 tok/s. Keep context short and close other GPU apps.
How much VRAM does Llama 3.1 8B need?
About 5.5 GB of weights at Q4_K_M, 10 GB at Q8_0 and 16 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.
How fast is Llama 3.1 8B on the RTX 5060?
Roughly 47 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX 5060's 448 GB/s memory bandwidth.