GPU Fit Matrix
Can the RTX 5060 Ti 16GB run Llama 3.1 8B Instruct?
Yes — fits at FP8
Planning estimate: Llama 3.1 8B Instruct (8B total) needs about10.5 GB of VRAM at FP8(≈4K context). The RTX 5060 Ti 16GB has16 GB.
This is a computed planning estimate (parameter count × bytes/parameter × quantization + context overhead), not a measured benchmark. See how we estimate.
VRAM needed by quantization
| Quantization | Est. VRAM needed | Fits 16GB? |
|---|---|---|
| BF16 | 18.5 GB | ❌ No |
| FP16 | 18.5 GB | ❌ No |
| FP8 | 10.5 GB | ✅ Yes |
No measured benchmark yet. We don't publish invented tokens/sec — when we have a first-party measured run for this pairing, it will appear here. For now this page is a VRAM planning estimate. Model the exact case in ourVRAM calculator.
Related
- VRAM calculator — tweak quantization and context for this exact model
- How much VRAM do you need?
- Best GPU for local LLMs
- All GPU × model fit pages