The RTX 5060 Ti comes in two memory sizes, 16 GB and 8 GB, both GDDR7 on a 128-bit bus with 4,608 CUDA cores, 448 GB/s of bandwidth, 759 AI TOPS and 180 W total graphics power. NVIDIA's launch list prices on April 16, 2025 were $429 for the 16 GB version and $379 for the 8 GB version.
For AI, the 16 GB version is the one to consider and the 8 GB version is not. The extra 8 GB costs $50 at launch list prices and changes which models load at all.
TL;DR
- Buy the 16 GB version for AI. The 8 GB version only fits small models (8B at 4-bit, computed).
- 16 GB runs 8B at INT8 and 14B at INT4 (computed), the same models as the far pricier RTX 5070 Ti.
- The weak spot is bandwidth: 448 GB/s, half the 5070 Ti's 896 GB/s, so generation is slower for the same model.
- 180 W means almost any modern power supply works.
- It is the cheapest sensible card in this family for local LLMs and Stable Diffusion-class image models.
RTX 5060 Ti specs
| Spec | RTX 5060 Ti 16 GB | RTX 5060 Ti 8 GB | RTX 5070 Ti |
|---|---|---|---|
| CUDA cores | 4,608 | 4,608 | 8,960 |
| Memory | 16 GB GDDR7 | 8 GB GDDR7 | 16 GB GDDR7 |
| Memory bus | 128-bit | 128-bit | 256-bit |
| Memory bandwidth | 448 GB/s | 448 GB/s | 896 GB/s |
| AI TOPS (Tensor) | 759 | 759 | 1,406 |
| Total graphics power | 180 W | 180 W | 300 W |
| Launch list price | $429 | $379 | $749 (Feb. 2025) |
NVIDIA's RTX 5060 family page lists one column of specs for both memory sizes, and its launch announcement gives the two prices and the April 16 date. Street prices differ from launch list prices. The RTX 5060 Ti page tracks rental availability, and the 5060 Ti vs 5070 Ti compare page puts the two side by side.
What fits in 16 GB and 8 GB
Computed: weights equal parameters times bytes per parameter (FP16 is 2, INT8 is 1, INT4 is 0.5), plus 20% overhead for KV cache and runtime buffers (our assumption). See how much VRAM you need for LLMs for the formula.
| Model size | FP16 with overhead | INT8 with overhead | INT4 with overhead | 16 GB | 8 GB |
|---|---|---|---|---|---|
| 8B | 19.2 GB | 9.6 GB | 4.8 GB | INT8, INT4 | INT4 only |
| 14B | 33.6 GB | 16.8 GB | 8.4 GB | INT4 | None |
| 32B | 76.8 GB | 38.4 GB | 19.2 GB | None | None |
The 8 GB column is the reason to avoid that version for AI. An 8B model at 4-bit uses about 4.8 GB with overhead, leaving about 3 GB for context. A 14B model at 4-bit misses 8 GB by a small margin (8.4 GB with overhead). Browse more models with the VRAM calculator for the RTX 5070 Ti, which has the same 16 GB capacity.
The bandwidth trade-off
LLM token generation reads the weights from memory for every token, so bandwidth sets the ceiling on speed. The 5060 Ti's 448 GB/s is half the 5070 Ti's and a quarter of the RTX 5090's 1,792 GB/s (computed from NVIDIA's published figures). The card will load a 14B 4-bit model, but it will generate more slowly than the 5070 Ti does. We do not quote tokens per second because we have not opened a benchmark from a named source for this card.
Running local LLMs
Ollama and llama.cpp both support NVIDIA GPUs. Ollama's README gives:
curl -fsSL https://ollama.com/install.sh | sh
ollama run gemma4
llama.cpp's README shows a Hugging Face download and server in one command:
llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF
Choose a model that fits using the table above. See the Ollama guide and llama.cpp guide for full setup.
Image generation
Computed from the FLUX.1 dev model card (12 billion parameters): about 12 GB at 8-bit for the main transformer alone, which fits the 16 GB version only with text encoders kept in system memory, and does not fit 8 GB at all. SDXL-class models are much smaller and run on either size, with the 16 GB version giving more headroom for ComfyUI workflows that load several models at once.
Fine-tuning
QLoRA is the practical route (full fine-tuning needs roughly 18 bytes per parameter with AdamW). Computed: a 4-bit 8B base is about 4 GB of frozen weights, which fits the 16 GB version with room for adapters and activations at short sequence lengths. The 8 GB version is too tight for most real runs. Slower bandwidth means longer runs. See LoRA fine-tuning.
Who should buy it
- Buy the 16 GB version if you want the cheapest NVIDIA card that runs 14B models at 4-bit and learns the stack.
- Skip the 8 GB version for AI. The $50 launch price gap is the best money you will spend.
- Step up to the RTX 5070 Ti if generation speed matters. Same capacity, twice the bandwidth.
- Rent a bigger card if your model is over 16 GB.
For the wider picture across consumer cards, read consumer GPUs for AI and RTX 5090 for AI.
Rent today
Not sure 16 GB is enough? Check it on a rented card first. The box shows what is available now.
FAQ
How much VRAM does the RTX 5060 Ti have?
Two versions: 16 GB and 8 GB of GDDR7, both on a 128-bit bus, per NVIDIA.
Is the RTX 5060 Ti good for AI?
The 16 GB version is a good entry card for local LLMs up to 14B at 4-bit and for SDXL-class image models. The 8 GB version is limited to small models.
What was the RTX 5060 Ti launch price?
NVIDIA announced $429 for the 16 GB version and $379 for the 8 GB version, available from April 16, 2025. Street prices differ.
Can the RTX 5060 Ti run a 14B model?
The 16 GB version can at 4-bit (about 8.4 GB with overhead, computed). The 8 GB version cannot.
Is 448 GB/s of bandwidth enough?
It is enough to run models that fit, but it is half of the 5070 Ti's bandwidth, so expect slower generation.
Sources
- NVIDIA, GeForce RTX 5060 family: https://www.nvidia.com/en-us/geforce/graphics-cards/50-series/rtx-5060-family/
- NVIDIA, Compare GeForce graphics cards (bandwidth, TGP, AI TOPS): https://www.nvidia.com/en-us/geforce/graphics-cards/compare/
- NVIDIA, RTX 5060 launch announcement (prices, date): https://nvidianews.nvidia.com/news/nvidia-blackwell-geforce-rtx-arrives-for-every-gamer-starting-at-299
- NVIDIA, Ultimate guide to RTX 5060 and 5060 Ti: https://www.nvidia.com/en-us/geforce/news/ultimate-guide-to-5060/
- NVIDIA, RTX 50 series announcements (5070 Ti 896 GB/s, 5090 1792 GB/s): https://www.nvidia.com/en-us/geforce/news/rtx-50-series-graphics-cards-gpu-laptop-announcements/
- NVIDIA, Blackwell GeForce RTX 50 series launch (5070 Ti price): https://nvidianews.nvidia.com/news/nvidia-blackwell-geforce-rtx-50-series-opens-new-world-of-ai-computer-graphics
- Ollama README: https://github.com/ollama/ollama
- llama.cpp README: https://github.com/ggml-org/llama.cpp
- FLUX.1 dev model card: https://huggingface.co/black-forest-labs/FLUX.1-dev
