Both cards carry 16GB of VRAM, which means both fit the same models. The question is whether the RTX 5060 Ti’s newer architecture and GDDR7 memory justify the $205 price premium over the RTX 4060 Ti 16GB.
NVIDIA GeForce RTX 5060 Ti 16GB
16GB GDDR7GDDR7 memory delivers meaningfully higher token throughput on LLM inference. At ~$630 it is no longer a rounding error over the 4060 Ti 16GB, but the speed gain is real for daily LLM use.
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Spec comparison
| Spec | RTX 5060 Ti 16GB | RTX 4060 Ti 16GB |
|---|---|---|
| Architecture | Blackwell | Ada Lovelace |
| VRAM | 16GB GDDR7 | 16GB GDDR6 |
| Memory bandwidth | ~448 GB/s | ~288 GB/s |
| CUDA cores | 4,608 | 4,352 |
| TDP | ~165W | ~165W |
| Price | ~$630 | ~$425 |
| Release | 2025 | 2023 |
The headline number: 55% more memory bandwidth on the 5060 Ti. For LLM inference, bandwidth is the primary performance driver — it determines how fast weights move from VRAM to the GPU cores during token generation.
LLM inference performance (estimated)
Running Llama 3 8B at Q4_K_M with Ollama:
| GPU | ~Tok/s (7B Q4) | ~Tok/s (14B Q4) | 32B fits? |
|---|---|---|---|
| RTX 5060 Ti 16GB | ~42 tok/s | ~22 tok/s | No |
| RTX 4060 Ti 16GB | ~28 tok/s | ~15 tok/s | No |
| Difference | +50% | +47% | — |
The bandwidth gap translates almost 1:1 into inference speed gains. On 7B models, the 5060 Ti produces roughly 14 more tokens per second. That is a meaningful improvement for interactive chat.
Neither card fits 32B models at Q4_K_M — both are 16GB cards. The ceiling is the same: 7B to 14B models comfortably, tight at 20GB+ models.
Check RTX 4060 Ti 16GB Price→Buy on Shopee SG→What you can run on 16GB
Both cards handle the same model sizes:
| Model | Size | Fits in 16GB? |
|---|---|---|
| Llama 3 8B | Q4_K_M 4.9GB | Yes, comfortably |
| Llama 3 8B | Q8 8.5GB | Yes |
| Qwen 3 14B | Q4_K_M 9.3GB | Yes, with context room |
| Qwen 3 14B | Q8 16GB | No — the weights alone fill the card |
| Mistral 7B | Q4_K_M 4.4GB | Yes, easily |
| Phi-4 14B | Q4_K_M ~9GB | Yes |
| Qwen 3 32B | Q4_K_M 20GB | No |
16GB is a solid tier for 7B to 14B models. You will not be running 32B on either card.
GDDR7 vs GDDR6: why it matters for LLMs
LLM inference is bandwidth-bound, not compute-bound. When generating tokens, the GPU streams model weights from VRAM repeatedly — once per token. A larger bandwidth pipe means more tokens per second, period.
GDDR7 on the 5060 Ti runs at a higher data rate than GDDR6 on the 4060 Ti, resulting in ~448 GB/s vs ~288 GB/s effective bandwidth. That 55% gap in bandwidth shows up directly as faster token generation.
Which GPU should YOU buy?
- Budget is the priority (~$425)? Get the RTX 4060 Ti 16GB. Same model support, only slower inference. Perfectly usable at ~28 tok/s on 7B models — still conversational speed.
- You run LLMs daily and want better throughput (~$630)? Get the RTX 5060 Ti. The ~50% token speed improvement is real. Conversations feel more responsive, especially on 14B models.
- You want to run 32B+ models? Neither card works. Save for an RTX 4090 (24GB). Both 16GB cards hit the same wall on large models.
- Building a budget LLM rig under $500? RTX 4060 Ti 16GB at ~$425 — it is the only one of the two that fits. The 5060 Ti has moved to ~$630 and is a different budget now, not a small step up.
Common mistakes to avoid
- Buying either card expecting to run 32B models. Both are 16GB cards. Qwen 3 32B is a 20GB download at Q4_K_M, so it needs a 24GB card once context is added. Neither of these gets there.
- Dismissing the 4060 Ti because it’s older. At ~$425 it still produces conversational-speed inference on 7B-14B models, and it now saves you $205 rather than $50 — enough that it deserves a serious look.
- Choosing the 5060 Ti solely for the architecture. Blackwell is newer, but the practical difference for consumer LLM workloads comes from bandwidth — not shader improvements.
- Ignoring the 8GB variant trap. Both cards have 8GB variants at lower prices. The 8GB versions are significantly more limited for LLMs. Always verify you are looking at the 16GB models.
Final verdict
| You want | Best pick | Price |
|---|---|---|
| Best speed on 7B-14B models | RTX 5060 Ti 16GB | ~$630 |
| Lowest cost for 16GB VRAM | RTX 4060 Ti 16GB | ~$425 |
| Step up to 32B models | RTX 4090 | ~$2,200 |
The RTX 5060 Ti wins on raw LLM throughput. The RTX 4060 Ti 16GB wins on price-per-VRAM. Both cap out at the same 14B-ish model ceiling. Choose based on whether faster inference is worth $205 to you — a question with a much less obvious answer than when the gap was $50.
NVIDIA GeForce RTX 5060 Ti 16GB
16GB GDDR7GDDR7 bandwidth gives ~50% faster token generation over the 4060 Ti, now for $205 more. Worth it if you run models daily; hard to justify if you do not.
Affiliate links — we may earn a commission at no extra cost to you. Amazon ships globally; Shopee SG covers Singapore & ASEAN.
For broader context on 16GB card options, see our best GPU for LLM under $500 guide. Running 7B models specifically? Check best GPU for 7B models. On a tighter budget? Our best budget GPU for local LLM guide covers all the options under $400.