GPU for local LLM · budget
NVIDIA GeForce RTX 4060 Ti 16GB
The cheapest brand-new 16GB card, if you can forgive the slow memory.
- VRAM
- 16 GB
- TDP
- 165 W
- Bandwidth
- 288 GB/s
- £ / GB
- £25
What it runs
With 16 GB you can comfortably load, at 4-bit quantisation, a dense model up to roughly
~28B params
Verdict
16GB new-with-warranty at low power, held back by memory bandwidth that caps inference speed.
BEST FOR
- + quiet always-on boxes
- + 16GB on a warranty
- + low-power low-fuss builds
NOT FOR
- - fast inference
- - long-document work
- - anyone chasing tokens per second
The RTX 4060 Ti 16GB is the cheapest brand-new card that hands you a proper 16GB of VRAM for local LLMs. It’s low-power, quiet, and it fits almost anywhere. Just don’t expect it to be quick; the memory bandwidth is where the budget bites, and it bites hard.
The take
Buy it for 16GB on a warranty at low wattage, not for speed. The extra memory lets you hold models a 12GB card can’t, and 165W means it sips power and runs cool enough to forget about. But the 288 GB/s memory bandwidth is slow for inference, and inference speed lives and dies on bandwidth. So you get the capacity without the pace. For a quiet, always-on box that values headroom over throughput, that trade can be exactly the right one.
What it’ll actually run
Sixteen gigabytes opens up 14B models at Q4 with a comfortable context, and it’ll take a 32B at a tight quant if you’re patient. Smaller 7B to 8B models sit in VRAM with plenty of room to spare. The capacity is properly useful and a clear step past the 12GB crowd, which is the reason anyone reaches for this card.
The catch is speed. That 288 GB/s bandwidth caps throughput hard, so expect something like 15 to 25 tokens/sec on a 7B at Q4 and single figures to low teens on a 14B. Fine for chat and coding help, frustrating for long documents or batch work. It’s the capacity of a much dearer card at the pace of a cheap one, and no amount of tuning changes that; the memory bus is what it is. On value, around £400 for 16GB is roughly £25 per gigabyte, respectable for a new card with a warranty, and the low 165W board power makes it the easy pick for a machine that runs all day without heating the room or spinning fans up. Drivers are current Ada CUDA, so every inference stack works with no fuss.
Who should buy it, and who shouldn’t
Buy it if you want new-with-warranty 16GB, low power, and a quiet build, and you’re happy trading speed for capacity and peace of mind. It’s the friendliest card here to live with: one 8-pin, two slots, cool and near-silent. First-timers who want to run 14B models without any used-market worry are the sweet spot.
Skip it if speed matters at all; a used 3090 gives you more VRAM and far more bandwidth for similar money, if you’ll accept the used market. And if you want properly fast 16GB and can spend, the 5080 is quicker by a mile at several times the price. But as the cheap, cool, capacious new option, the 4060 Ti 16GB has a real place.
Settings people actually run
The configs owners land on, pulled from the community. A sensible starting point, not gospel - tune to your own kit.
16GB on a warranty, low power
Q4_K_M 14B, comfortable context
Capacity of a much dearer card at 165W and near silent; a clear step past the 12GB crowd.
32B if you are patient
tight quant, modest context
Possible rather than pleasant; the 288 GB/s bus caps token generation hard.
Quiet always-on box
single 8-pin, one card
Cool and quiet enough to forget about; the friendliest card here to live with.
What owners report
Real first-hand experience gathered from owners and the community.
- “
Owners find the 4060 Ti 16GB severely bottlenecked by memory bandwidth: 288 GB/s against the 3090's 936 GB/s. It loads bigger models than a 12GB card but generates tokens slowly, so expect the low double figures on a 7B and single figures on a 14B.
- “
It fits the same models as a 16GB 4080 (Llama 3.1 8B, Gemma 3 12B QAT, Mixtral Q4 with offload) but runs them noticeably slower thanks to fewer CUDA cores and the narrow bus; Llama 3.1 8B is the comfortable everyday pick.
1 claim(s) we couldn't fully verify
- · typical price around GBP 400 / USD 450 (mid-2026) - New-card street price moves with stock and tariffs; figure is indicative only.
Hands-on reviews we drew on
We don't just copy the spec sheet. These are the teardowns and hands-on reviews behind this page - worth watching in their own right.
- Best Local LLMs for Every NVIDIA RTX 40 Series GPUApX Machine Learning · review
- Some graphs comparing the RTX 4060 Ti 16GB and the 3090 for LLMsr/LocalLLaMA · thread
- GeForce RTX 4060 Ti 16 GB specificationsTechPowerUp · primary source
Common questions
Why is the 4060 Ti 16GB slow for LLMs when it has 16GB?+
Because inference speed lives on memory bandwidth, and this card only has 288 GB/s. The 16GB lets you hold bigger models than a 12GB card, but the narrow memory bus means data moves through it slowly. You get the capacity without the pace, which is the card's whole character.
Is the 16GB 4060 Ti better than a used 3090 for AI?+
Only on power draw, noise, and having a warranty. The 3090 has more VRAM and roughly three times the bandwidth, so it runs bigger models much faster. Pick the 4060 Ti if you want new, cool and quiet; pick the 3090 if you want speed and headroom and you'll accept the used market.
Can it run a 32B model?+
At a tight quant, with a modest context, yes, but slowly. 14B at Q4 is the comfortable ceiling for everyday use. Treat 32B as possible rather than pleasant on this card.
