Compare · GPUs
RTX 3060 vs RTX 4060 Ti for local LLMs
It runs 21 of 39 models fully in memory, against 16 for the RTX 3060, thanks to 16 GB of VRAM versus 12 GB. The RTX 3060 is about 32% faster on the models both can hold, so it only wins if you stick to small models.
It runs 21 of 39 models fully in memory, against 16 for the RTX 3060, thanks to 16 GB of VRAM versus 12 GB. The RTX 3060 is about 32% faster on the models both can hold, so it only wins if you stick to small models.
Every model at 8K context with the best quantization that fits. Offload assumes 32 GB of system RAM. Green marks the better result. Rows where the two differ come first.
| Model | RTX 3060 | RTX 4060 Ti |
|---|---|---|
| Gemma 3 12B | Offload~4.9 tok/sQ4_K_M | Runs~19 tok/sQ6_K |
| Phi-4 14B | Offload~4.0 tok/sQ4_K_M | Runs~18 tok/sQ5_K_M |
| Qwen3 14B | Offload~4.0 tok/sQ4_K_M | Runs~18 tok/sQ5_K_M |
| DeepSeek-R1 Distill 14B | Offload~4.0 tok/sQ4_K_M | Runs~18 tok/sQ5_K_M |
| gpt-oss 20B | Offload~8.6 tok/sQ4_K_M | Runs~39 tok/sQ4_K_M |
| Qwen3 0.6B | Runs~370 tok/sQ8_0 | Runs~290 tok/sQ8_0 |
| Gemma 3 1B | Runs~220 tok/sQ8_0 | Runs~180 tok/sQ8_0 |
| Llama 3.2 1B | Runs~180 tok/sQ8_0 | Runs~150 tok/sQ8_0 |
| Llama 3.2 3B | Runs~69 tok/sQ8_0 | Runs~55 tok/sQ8_0 |
| Phi-4 Mini 3.8B | Runs~58 tok/sQ8_0 | Runs~47 tok/sQ8_0 |
| Qwen3 4B | Runs~55 tok/sQ8_0 | Runs~44 tok/sQ8_0 |
| Gemma 3 4B | Runs~51 tok/sQ8_0 | Runs~41 tok/sQ8_0 |
| Qwen3.5 4B | Runs~47 tok/sQ8_0 | Runs~38 tok/sQ8_0 |
| Mistral 7B v0.3 | Runs~31 tok/sQ8_0 | Runs~25 tok/sQ8_0 |
| Qwen2.5-Coder 7B | Runs~29 tok/sQ8_0 | Runs~23 tok/sQ8_0 |
| Llama 3.1 8B | Runs~28 tok/sQ8_0 | Runs~22 tok/sQ8_0 |
| DeepSeek-R1 Distill 8B | Runs~28 tok/sQ8_0 | Runs~22 tok/sQ8_0 |
| Qwen3 8B | Runs~27 tok/sQ8_0 | Runs~22 tok/sQ8_0 |
| Qwen3.5 9B | Runs~30 tok/sQ6_K | Runs~19 tok/sQ8_0 |
| Gemma 4 12B | Runs~33 tok/sQ4_K_M | Runs~19 tok/sQ6_K |
| Mistral Nemo 12B | Runs~33 tok/sQ4_K_M | Runs~19 tok/sQ6_K |
| Codestral 22B | Offload~2.7 tok/sQ4_K_M | Offload~2.2 tok/sQ4_K_M |
| Mistral Small 3 24B | Offload~2.5 tok/sQ4_K_M | Offload~2.1 tok/sQ4_K_M |
| Devstral Small 24B | Offload~2.5 tok/sQ4_K_M | Offload~2.1 tok/sQ4_K_M |
| Gemma 4 26B-A4B (MoE) | Offload~8.7 tok/sQ4_K_M | Offload~6.7 tok/sQ4_K_M |
| Gemma 3 27B | Offload~2.2 tok/sQ4_K_M | Offload~1.9 tok/sQ4_K_M |
| Qwen3.6 27B | Offload~2.2 tok/sQ4_K_M | Offload~1.8 tok/sQ4_K_M |
| Qwen3 30B-A3B (MoE) | Offload~10 tok/sQ4_K_M | Offload~7.9 tok/sQ4_K_M |
| Qwen3-Coder 30B-A3B | Offload~10 tok/sQ4_K_M | Offload~7.9 tok/sQ4_K_M |
| Gemma 4 31B | Offload~1.9 tok/sQ4_K_M | Offload~1.7 tok/sQ4_K_M |
| Qwen3 32B | Offload~1.8 tok/sQ4_K_M | Offload~1.6 tok/sQ4_K_M |
| DeepSeek-R1 Distill 32B | Offload~1.8 tok/sQ4_K_M | Offload~1.6 tok/sQ4_K_M |
| Qwen2.5-Coder 32B | Offload~1.8 tok/sQ4_K_M | Offload~1.6 tok/sQ4_K_M |
| Qwen3.6 35B-A3B (MoE) | Offload~11 tok/sQ4_K_M | Offload~8.8 tok/sQ4_K_M |
| Llama 3.3 70B | Won’t fit | Won’t fit |
| DeepSeek-R1 Distill 70B | Won’t fit | Won’t fit |
| Llama 4 Scout 109B-A17B | Won’t fit | Won’t fit |
| gpt-oss 120B | Won’t fit | Won’t fit |
| Qwen3 235B-A22B (MoE) | Won’t fit | Won’t fit |
Which should you buy?
The RTX 4060 Ti is the better card for local AI. It runs 21 of 39 models fully in memory, against 16 for the RTX 3060, thanks to 16 GB of VRAM versus 12 GB. The RTX 3060 is about 32% faster on the models both can hold, so it only wins if you stick to small models.
Only the RTX 4060 Ti fits Gemma 3 12B, Phi-4 14B, Qwen3 14B, DeepSeek-R1 Distill 14B and gpt-oss 20B fully in memory.
See every result on its own page: RTX 3060 and RTX 4060 Ti.
Questions
Is the RTX 3060 or the RTX 4060 Ti better for running LLMs?
The RTX 4060 Ti is the better card for local AI. It runs 21 of 39 models fully in memory, against 16 for the RTX 3060, thanks to 16 GB of VRAM versus 12 GB. The RTX 3060 is about 32% faster on the models both can hold, so it only wins if you stick to small models.
Which models can the RTX 4060 Ti run that the RTX 3060 can't?
At 8K context, only the RTX 4060 Ti holds Gemma 3 12B, Phi-4 14B, Qwen3 14B, DeepSeek-R1 Distill 14B and gpt-oss 20B fully in VRAM.
Does the RTX 3060 or RTX 4060 Ti need anything else to run local AI?
Only the software. Install Ollama or LM Studio, pick a model that fits in VRAM, and it runs on the GPU. 32 GB of system RAM helps when a model spills over, but that path is much slower.
More comparisons
Estimates from memory size and bandwidth at 8K context. Real speed varies with software, drivers and settings.