The RTX 5060 Ti 16GB is capable for fine-tuning 7B-13B models with the right technique. Our hosting gives you full root, so you can run any stack. Training throughput numbers below.
Contents
What Fits in 16 GB
| Technique | Max model (reliable) | Max sequence |
|---|---|---|
| Full fine-tune | 1.5B | 2048 |
| LoRA (FP16) | 7B | 4096 |
| QLoRA (4-bit) | 13B | 4096 |
| Unsloth QLoRA | 13B | 8192 |
LoRA Throughput (samples/sec)
| Model | Seq len | Batch | samples/s |
|---|---|---|---|
| Mistral 7B | 2048 | 1 | 1.8 |
| Mistral 7B | 2048 | 4 | 5.2 |
| Llama 3 8B | 2048 | 1 | 1.6 |
| Llama 3 8B | 2048 | 4 | 4.6 |
QLoRA Throughput
| Model | Seq len | Batch | samples/s |
|---|---|---|---|
| Llama 3 8B | 2048 | 4 | 3.8 |
| Llama 3 8B | 4096 | 2 | 1.9 |
| Qwen 2.5 14B | 2048 | 2 | 1.5 |
| Qwen 2.5 14B | 4096 | 1 | 0.9 |
Unsloth
| Model | Seq len | Batch | Unsloth samples/s | Uplift vs vanilla |
|---|---|---|---|---|
| Llama 3 8B QLoRA | 2048 | 4 | 6.8 | 1.8x |
| Qwen 2.5 14B QLoRA | 2048 | 2 | 2.7 | 1.8x |
Unsloth’s custom Triton kernels give a clean ~1.8-2x on this card. For any Blackwell fine-tune on a single GPU, use Unsloth.
Practical Fine-Tune Times
- Llama 3 8B QLoRA on 10k samples @ seq 2048: ~35 min with Unsloth
- Mistral 7B LoRA on 50k samples @ seq 2048: ~2.5 hours
- Qwen 2.5 14B QLoRA on 10k samples: ~1 hour with Unsloth
Full epoch on a mid-size dataset (~50-100k samples) runs overnight.
Fine-Tuning on Blackwell 16GB
Llama 3 8B QLoRA in 35 min per 10k samples. UK dedicated hosting.
Order the RTX 5060 Ti 16GBSee also: QLoRA speed, LoRA speed, Unsloth speed, LoRA guide, QLoRA guide.
