Best local AI model for RTX 4060 Ti 16GB.

The best quality-per-fit default at 16GB. Run Qwen3-14B at Q4/Q5 rather than crushing a 32B model into degraded quant and short context. Old 8B/12B rows are fallback, not the winner here.

Recommendation Full matrix

01 / Recommendation

Run this size class.

Recommended default

Qwen3-14B

Use Q4/Q5 GGUF, 16k-32k practical. This is the highest-scoring current open-weight model that fits this card cleanly, selected by benchmark then fit then freshness, not by parameter count.

Benchmark anchor

Qwen3-14B is the stronger current small-mid baseline; clearly ahead of legacy Mistral/Llama 8B-12B rows on reasoning and coding.

Evidence

Qwen3 family is the stronger current baseline at this size; legacy 70B baselines are irrelevant on a 16GB card.

02 / Alternates

Other realistic picks.

Qwen3-8B at higher quant

Mistral Nemo 12B (legacy)

Llama 3.1 8B (legacy fallback)

03 / More GPUs

Compare another card.

RTX 3060 12GB RTX 5080 16GB RTX 3090 24GB RTX 4090 24GB RTX 5090 32GB