▚ whichaipc

GPU for local LLM · upper-mid

NVIDIA GeForce RTX 5070 Ti

16GB of GDDR7 and current-gen speed, the sensible new card for single-GPU local AI.

VRAM
16 GB
TDP
300 W
Bandwidth
896 GB/s
£ / GB
£44

What it runs

With 16 GB you can comfortably load, at 4-bit quantisation, a dense model up to roughly

~28B params

Verdict

A quick, efficient 16GB card that runs anything up to a tight 32B, if 16GB is enough for you.

BEST FOR

  • + fast 7B to 14B models
  • + new-with-warranty buyers
  • + one-slot 300W builds

NOT FOR

  • - 24GB and 32B-at-quality work
  • - value-per-pound VRAM
  • - 70B ambitions

If you want a current card for running LLMs at home and you don’t need 24GB, the RTX 5070 Ti is the sensible pick. Sixteen gigabytes of GDDR7, Blackwell speed, and a 300W draw that won’t cook your case. It’s the card I’d point most first-time local-AI builders at when they want new-with-warranty rather than used-market roulette.

The take

You’re buying speed and efficiency, not capacity. At 896 GB/s the 5070 Ti moves tokens quickly, and bandwidth is what sets generation speed, so it feels brisk on anything that fits. The catch is the 16GB ceiling. That’s fine until the day you want a 32B at proper quant or a 70B, and then it isn’t. Know which side of that line you sit on before you spend.

What it’ll actually run

Sixteen gigabytes is the comfortable home for 7B to 14B models, and that’s the class most people reach for daily. A 14B at Q4 sits inside VRAM with a generous context and replies faster than you can read. Smaller 7B models feel instant.

Push to a 32B and you’re right at the edge. It’ll load at a tight quant with a trimmed context, but you’re making compromises a 24GB card doesn’t ask for. A 70B is off the table without heavy CPU offload, which drags speed down hard. Brilliant up to 14B, workable at 32B if you’re careful, wrong tool for anything bigger.

On efficiency it’s a strong showing. Three hundred watts is modest for a current-gen card, and since inference is bandwidth bound you can power limit it to around 230W and lose almost nothing. Quiet, cool, tidy. That matters if this box lives in your office and stays on.

Who should buy it, and who shouldn’t

Buy it if you want a new, efficient, current-gen card and 16GB covers your models. It suits people running assistants and coding models in the 7B to 14B range who value a warranty and a build that drops into a 750W system without drama. Two slots, one connector, done.

Skip it if you know you want 24GB. For 32B-at-quality or the option of a 70B across two cards, a used 3090 gives you more usable VRAM per pound, and a 5090 gives you both speed and 32GB if budget allows. But for the person who wants current, quiet, and enough, the 5070 Ti fits the brief.

Settings people actually run

The configs owners land on, pulled from the community. A sensible starting point, not gospel - tune to your own kit.

Fast small model

Qwen2.5 7B or 14B at Q4_K_M in LM Studio

Sits well inside 16GB with a large context and runs far above reading speed on Blackwell's bandwidth.

32B at the limit

A 32B at Q3 to Q4 with a modest context

Fits only tightly; you trade context length or quant quality to keep it in 16GB. This is where a 24GB card pulls ahead.

Efficient inference

nvidia-smi power limit around 220-250W

Generation is bandwidth bound, so trimming the 300W cap costs little throughput and drops heat and noise.

Fact-checked 19 Jul 20269 claims verified against primary sources.
1 claim(s) we couldn't fully verify
  • · indicative price around GBP 700 / USD 750 (mid-2026) - No primary source (NVIDIA or TechPowerUp) tracks street pricing; 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.

Common questions

Is 16GB enough for local LLMs in 2026?+

For 7B to 14B models it's plenty, and those cover most day-to-day assistant and coding work. A 32B fits only at a tight quant with a modest context, and a 70B doesn't fit at all without heavy offload. If you know you want 32B at quality or bigger, a 24GB card is the better buy.

How does the 5070 Ti compare to a used 3090 for AI?+

The 5070 Ti is newer, faster per watt, quieter, and comes with a warranty, but it gives you 16GB against the 3090's 24GB. For raw model size the 3090 wins; for a tidy, efficient, current-gen box the 5070 Ti wins. It's speed and support versus capacity.

What power supply does it need?+

At 300W board power it's undemanding by current-gen standards. A quality 750W PSU runs a full system comfortably. Reference cards use a single 16-pin connector; many partner cards ship with 2 to 3x 8-pin instead, so check the model before you buy cables.