microsoft/Phi-3-medium-4k-instruct
14B params · est. 8.4 GB Q4
NVIDIA GeForce RTX 5060 Ti 16GB: likely fitNVIDIA GeForce RTX 4060 Ti 16GB: likely fit
Head-to-head
NVIDIA GeForce RTX 5060 Ti 16GB vs NVIDIA GeForce RTX 4060 Ti 16GB
Dedicated comparison page for two real hardware profiles. This is built from your benchmark database, trust metadata, and buyer flow instead of generic spec-sheet comparisons.
Device profile
NVIDIA GeForce RTX 5060 Ti 16GB
Compared here against NVIDIA GeForce RTX 4060 Ti 16GB.
Curated Aggregate·2026-04-2216GB / $449
Best LLM
132 tok/s
VRAM
16 GB
TDP
180 W
Rating
8.5
Device profile
NVIDIA GeForce RTX 4060 Ti 16GB
13B Q4 full-GPU at 25-30 tok/s — the 16GB headroom matters more than speed at this price
Curated Aggregate·2025-05-0116GB / $499
Best LLM
56.0 tok/s
VRAM
16 GB
TDP
165 W
Rating
8.3
Quick verdict
NVIDIA GeForce RTX 5060 Ti 16GB scores 8.5 while NVIDIA GeForce RTX 4060 Ti 16GB scores 8.3 on MyAIHardware's composite rating.
VRAM capacity is tied.
NVIDIA GeForce RTX 4060 Ti 16GB is the lower-power path.
On shared workload evidence, Llama 3 8B Q4 is benchmarked at 72.0 tok/s for NVIDIA GeForce RTX 5060 Ti 16GB and 48.0 tok/s for NVIDIA GeForce RTX 4060 Ti 16GB.
| Metric | NVIDIA GeForce RTX 5060 Ti 16GB | NVIDIA GeForce RTX 4060 Ti 16GB |
|---|---|---|
| MyAI rating | 8.5 | 8.3 |
| Best LLM | 132 tok/s | 56.0 tok/s |
| VRAM | 16 GB | 16 GB |
| TDP | 180 W | 165 W |
| MSRP | $449 | $499 |
| Workloads | 5 | 6 |
Shared benchmark rows
Llama 3 8B Q4
Llama 3 8B Q4
NVIDIA GeForce RTX 5060 Ti 16GB
72.0 tok/s
Q4_K_M / 16GB / 2026-04-10
NVIDIA GeForce RTX 4060 Ti 16GB
48.0 tok/s
Q4_K_M / 16GB / 2024-08-12
Mistral 7B Q4
Mistral 7B
NVIDIA GeForce RTX 5060 Ti 16GB
68.0 tok/s
Q4_K_M / 16GB / 2026-04-14
NVIDIA GeForce RTX 4060 Ti 16GB
56.0 tok/s
Q4_K_M / 16GB / 2024-09-03
Gemma 2 9B Q4
Gemma 2 9B
NVIDIA GeForce RTX 5060 Ti 16GB
62.0 tok/s
Q4_K_M / 16GB / 2025-04-26
NVIDIA GeForce RTX 4060 Ti 16GB
47.0 tok/s
Q4_K_M / 16GB / 2024-08-04
External quality layer
Best open models likely to fit this class
This shortlist cross-references the external OpenEvals snapshot with an approximate Q4-class VRAM estimate. Use it to sanity-check whether the hardware you are comparing can host strong open models, not just benchmark toy workloads.
91.0
microsoft/Phi-3.5-mini-instruct
3.8B params · est. 2.3 GB Q4
NVIDIA GeForce RTX 5060 Ti 16GB: likely fitNVIDIA GeForce RTX 4060 Ti 16GB: likely fit
internlm/internlm2_5-7b-chat
7.7B params · est. 4.6 GB Q4
NVIDIA GeForce RTX 5060 Ti 16GB: likely fitNVIDIA GeForce RTX 4060 Ti 16GB: likely fit
microsoft/Phi-3-mini-4k-instruct
3.8B params · est. 2.3 GB Q4
NVIDIA GeForce RTX 5060 Ti 16GB: likely fitNVIDIA GeForce RTX 4060 Ti 16GB: likely fit