The RTX 4060 Ti 16GB offers entry-level 16GB VRAM at an affordable price. Despite lower bandwidth than newer cards, its 16GB capacity allows running 14B parameter models that 12GB cards cannot. A solid choice for users who need larger models on a budget.
16GB VRAM opens the door to 14B parameter models at Q4 quantization. DeepSeek-R1 14B, Qwen 2.5 14B, and other mid-size models use about 9-10GB, fitting comfortably. The main limitation is bandwidth: at 288 GB/s, the 4060 Ti is slower per-token than the RTX 3060 despite being a newer card. Think of it as a capacity card, not a speed card. If you plan to run 14B models, the extra 4GB of VRAM matters more than raw speed.
| GPU | VRAM | Speed | Bandwidth | Price |
|---|---|---|---|---|
| RTX 3060 | 12 GB | 42 tok/s | 360 GB/s | $250 |
| RTX 4060 Ti | 16 GB | 34 tok/s | 288 GB/s | $409 |
| RTX 5060 Ti | 16 GB | 51 tok/s | 448 GB/s | $430 |
| RTX 4070 Ti SUPER | 16 GB | 72 tok/s | 672 GB/s | $1,148 |
Llama / 8B / Q4_K_M / ~6.5 GB
Best for: Chat, Coding·Pop: 94/100
Perf: ~34.0 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4060 Ti.
ollama run llama3.1:8b-instruct-q4_K_M
Qwen / 9B / Q4_K_M / ~7 GB
Best for: Quality, Coding, Reasoning·Pop: 86/100
Perf: ~30.8 tok/s · first token ~0.5s
Fits in 16 GB VRAM with room to spare. Best for quality, coding, reasoning on RTX 4060 Ti.
ollama run qwen3.5:9b-instruct-q4_K_M
Qwen / 8B / Q4_K_M / ~6.5 GB
Best for: Chat, Coding·Pop: 88/100
Perf: ~34.0 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4060 Ti.
ollama run qwen3:8b-q4_K_M
Mistral / 7B / Q4_K_M / ~5.5 GB
Best for: Chat, Coding·Pop: 90/100
Perf: ~38.1 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4060 Ti.
ollama run mistral:7b-instruct-q4_K_M
Qwen / 7B / Q4_K_M / ~5.5 GB
Best for: Coding·Pop: 85/100
Perf: ~38.1 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for coding on RTX 4060 Ti.
ollama run qwen2.5-coder:7b-q4_K_M
Qwen / 7B / Q4_K_M / ~5.5 GB
Best for: Chat, Coding·Pop: 86/100
Perf: ~38.1 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4060 Ti.
ollama run qwen2.5:7b-instruct-q4_K_M
LFM2 / 8B / Q4_K_M / ~6 GB
Best for: Local agents, tool calling, fast chat·Pop: 75/100
Perf: ~34.0 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for local agents, tool calling, fast chat on RTX 4060 Ti.
ollama run liquidai/lfm2:8b-a1b-instruct-q4_K_M
DeepSeek / 7B / Q4_K_M / ~5.5 GB
Best for: Reasoning, Coding·Pop: 77/100
Perf: ~38.1 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for reasoning, coding on RTX 4060 Ti.
ollama run deepseek-r1-distill:qwen-7b-q4_K_M
Llama / 8B / Q5_K_M / ~8 GB
Best for: Chat, Coding·Pop: 82/100
Perf: ~29.2 tok/s · first token ~0.5s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4060 Ti.
ollama run llama3.1:8b-instruct-q5_K_M
Gemma / 9B / Q4_K_M / ~7 GB
Best for: Chat, Coding·Pop: 81/100
Perf: ~30.8 tok/s · first token ~0.5s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4060 Ti.
ollama run gemma2:9b-instruct-q4_K_M
Alibaba Cloud — Widest size range (0.5B to 235B)
LlamaMeta — Most popular open-weight model family
DeepSeekDeepSeek AI — Best-in-class reasoning with R1 models
MistralMistral AI — Excellent performance-per-parameter ratio
GemmaGoogle DeepMind — Excellent quality at small sizes (1B-9B)
PhiMicrosoft — Best quality-per-parameter in small sizes
The RTX 4060 Ti comes in 8GB and 16GB variants. For local AI, you need the 16GB version. It provides about 15.5GB usable VRAM after overhead, enough to load 14B parameter models at Q4 quantization.
Up to 14B parameter models at Q4 quantization. This includes DeepSeek-R1 14B, Qwen 2.5 14B, and Phi-3 14B. Smaller 7B models run with plenty of room for longer context windows.
It depends on what you need. The 16GB variant is excellent for running 14B models on a budget. However, its low memory bandwidth (288 GB/s) makes it slower than the RTX 3060 for 7B models. Choose it for model size, not speed.
The RTX 5060 Ti (16GB GDDR7) is 50% faster at 51 tok/s vs 34 tok/s, thanks to GDDR7 bandwidth (448 vs 288 GB/s). At similar pricing, the 5060 Ti is the clear winner if you can find one in stock.
Use our interactive wizard to compare models across Apple Silicon and NVIDIA GPUs.