RTX 4060 Ti 16GB vs RTX 5060 Ti 16GB for Local LLMs
Both have 16.0 GB, so they run the same models. The RTX 5060 Ti 16GB generates tokens about 55% faster. Below: speeds on seven popular models, the models only one card can run, and our verdict.
Specs that matter for AI
| RTX 4060 Ti 16GB | RTX 5060 Ti 16GB | |
|---|---|---|
| Memory | 16 GB | 16 GB |
| GPU-usable memory | 16.0 GB | 16.0 GB |
| Bandwidth | 288 GB/s | 448 GB/s |
| Architecture | Ada Lovelace | Blackwell |
| Released | 2023-07 | 2025-04 |
| Llama 3.1 8B Q4_K_M | ~34 tok/s | ~53 tok/s |
Speed and fit by model
Q4_K_M (or native format) with 8K context.
| Model | VRAM | RTX 4060 Ti 16GB | RTX 5060 Ti 16GB |
|---|---|---|---|
| Llama 3.1 8B | 6.3 GB | Fits ~34 tok/s | Fits ~53 tok/s |
| Qwen 3 14B | 10.5 GB | Fits ~19 tok/s | Fits ~30 tok/s |
| gpt-oss-20b | 13.9 GB | Fits ~64 tok/s | Fits ~92 tok/s |
| Qwen 3 30B-A3B | 18.8 GB | 80% on GPU ~38 tok/s | 80% on GPU ~44 tok/s |
| Qwen 3 32B | 21.4 GB | 70% on GPU ~4.4 tok/s | 70% on GPU ~5.0 tok/s |
| Llama 3.3 70B | 43.2 GB | 35% on GPU ~1.3 tok/s | 35% on GPU ~1.4 tok/s |
| gpt-oss-120b | 62.0 GB | Too small | Too small |
Verdict
Same 16 GB, so the same models fit. The 5060 Ti's GDDR7 gives 448 GB/s versus 288 GB/s, about 55% faster token generation. If both are similar in price, the 5060 Ti is the clear choice for local AI.
Which should you buy?
Choose the RTX 4060 Ti 16GB if…
- You find one used for clearly less than a new 5060 Ti.
- You already own one: the upgrade is speed only, not capacity.
Choose the RTX 5060 Ti 16GB if…
- You are buying new: same memory, far more bandwidth.
- You want FP4 support for newer image and LLM runtimes.
- You care about token speed on 14–20B models.
Best quality and longest context on each card
The highest-quality quantization that fits fully at 8K context, and the longest context that fits at Q4_K_M with an FP16 cache.
| Model | RTX 4060 Ti 16GB: best quant | RTX 5060 Ti 16GB: best quant | RTX 4060 Ti 16GB: max context | RTX 5060 Ti 16GB: max context |
|---|---|---|---|---|
| Qwen 3.5 9B | Q8_0 | Q8_0 | 256K | 256K |
| Qwen 3 14B | Q6_K | Q6_K | 37K | 37K |
| gpt-oss-20b | MXFP4 (official) | MXFP4 (official) | 55K | 55K |
| Qwen 3.6 27B | IQ4_XS | IQ4_XS | – | – |
| Qwen 3 32B | Q2_K | Q2_K | – | – |
| Llama 3.3 70B | Does not fit | Does not fit | – | – |
Image generation
Best weight precision for image models with model swapping, at each model's default resolution. Image generation is also limited by compute, so the card with more tensor-core throughput finishes each image faster even when both fit.
| Model | RTX 4060 Ti 16GB | RTX 5060 Ti 16GB |
|---|---|---|
| SDXL 1.0 | FP16 / BF16 | FP16 / BF16 |
| FLUX.1 [dev] | FP8 | FP8 |
| Qwen-Image | GGUF Q5_K_S | GGUF Q5_K_S |
| Wan 2.2 A14B (T2V / I2V) | GGUF Q5_K_S | GGUF Q5_K_S |
Frequently asked questions
Is the RTX 4060 Ti 16GB or RTX 5060 Ti 16GB better for local LLMs?
Same 16 GB, so the same models fit. The 5060 Ti's GDDR7 gives 448 GB/s versus 288 GB/s, about 55% faster token generation. If both are similar in price, the 5060 Ti is the clear choice for local AI.
Which is faster for LLM inference?
The RTX 5060 Ti 16GB, by about 55% for token generation on models that fit both (about 53 vs 34 tokens/s on Llama 3.1 8B Q4_K_M).
Which can run bigger models?
Neither: both have 16.0 GB usable, so they run the same models.