RTX 5070 Ti vs RTX 3090 for LLM: New $1,050 vs Used $820

RTX 5070 Ti (16GB GDDR7) vs used RTX 3090 (24GB GDDR6X) for local LLMs in 2026 — tok/s, VRAM, and which is the better buy.

Quick read: This guide is built to help you match model size, VRAM, and budget before you buy.

These two used to cost about the same. They do not any more: the RTX 5070 Ti is around $1,050 new, while a used RTX 3090 is around $820 — so the cheaper card is also the one with 50% more VRAM. That makes the 3090 the default for LLM work and turns this into a narrower question: what do you get for the extra $230, and is it worth giving up 8GB to have it?

Best for 7B-13B Speed

NVIDIA GeForce RTX 5070 Ti

16GB GDDR7

16GB GDDR7 with 5th-gen tensor cores. Faster architecture for small-to-mid models at ~$1,050 new with full warranty.

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Raw specs comparison

SpecRTX 5070 TiRTX 3090 (used)
VRAM16GB GDDR724GB GDDR6X
Memory bandwidth~896 GB/s~936 GB/s
Tensor cores5th gen3rd gen
TDP300W350W
Price~$1,050 new~$820 used
WarrantyFull manufacturerNone (used)
7B Q4 tok/s~45~55
13B Q4 tok/s~27~35

The 3090 is actually faster in raw tok/s on these models because its wider 384-bit memory bus and higher effective bandwidth feed tokens quickly. But the 5070 Ti’s newer architecture narrows that gap more than the numbers suggest — its tensor cores handle quantized inference more efficiently per watt.

VRAM capacity vs memory bandwidth
RTX 5090 32GB · 1792 GB/s RTX 4090 24GB · 1008 GB/s RX 7900 XTX 24GB · 960 GB/s RTX 3090 (used) 24GB · 936 GB/s RTX 5080 16GB · 960 GB/s RTX 5070 Ti 16GB · 896 GB/s RTX 4070 Ti Super 16GB · 672 GB/s RX 7800 XT 16GB · 624 GB/s RTX 5060 Ti 16GB 16GB · 448 GB/s RTX 4060 Ti 16GB 16GB · 288 GB/s RTX 5070 12GB · 672 GB/s Intel Arc B580 12GB · 456 GB/s RTX 3060 12GB (used) 12GB · 360 GB/s RTX 4060 8GB · 272 GB/s

VRAM capacity memory bandwidth Specs are manufacturer figures. Bar lengths are scaled independently per metric.

Where the 5070 Ti wins

For 7B and 13B parameter models — which covers Llama 3 8B, Mistral 7B, Phi-4, Qwen 2.5 14B (at Q4), and most coding assistants — 16GB is plenty. You won’t bump into VRAM limits, and the 5070 Ti runs cool, draws less power, and comes with a warranty.

The 5070 Ti is the better choice if you:

  • Run 7B-13B models as your daily driver
  • Want a new card with manufacturer warranty
  • Plan to use the GPU for gaming or creative work too
  • Don’t want to deal with used market risks

At 45 tok/s on 7B Q4, the 5070 Ti delivers fast, interactive responses. That’s well above the ~30 tok/s threshold where output feels instantaneous for chat use.

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Where the 3090 wins

The 3090’s 24GB advantage becomes decisive the moment you try to load a 34B model. CodeLlama 34B at Q4_K_M needs ~20GB of VRAM. Qwen 2.5 32B at Q4 needs ~19GB. The 5070 Ti simply cannot fit these models. The 3090 loads them with room to spare.

The 3090 is the better choice if you:

  • Want to run 30B-34B parameter models locally
  • Plan to add a second GPU later for 70B inference
  • Need headroom for larger context windows
  • Are comfortable buying used hardware

At ~35 tok/s on 13B and ~12-18 tok/s on 34B models, the 3090 handles heavier workloads that the 5070 Ti physically cannot attempt. For a full guide on buying one safely, see Used RTX 3090 Buying Guide.

Best for 34B Models

NVIDIA GeForce RTX 3090

24GB GDDR6X

24GB GDDR6X fits 34B models that no 16GB card can touch. At ~$820 used, it's the cheapest path to running large LLMs locally.

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The model size decision tree

This is how I frame it:

  • Only running 7B models? Either card works. Save money with an RTX 3060 12GB at $250 used.
  • Running 7B-13B regularly? 5070 Ti. Newer, faster per watt, and 16GB is sufficient.
  • Running 34B models? 3090. No alternative at this price. The next 24GB+ option is the RTX 4090 at ~$2,200. Wondering whether the cheaper non-Ti RTX 5070 might squeeze 34B in at all? See can the RTX 5070 run 34B? for the bad news at 12GB.
  • Planning multi-GPU later? 3090. Two 3090s give you 48GB combined for ~$1,640 — still less than a single RTX 4090 with half the VRAM — enough for 70B models.

Value per dollar

MetricRTX 5070 TiRTX 3090
Price~$1,050~$820
VRAM per dollar15.2 MB/$29.3 MB/$
7B tok/s per $1004.36.7
13B tok/s per $1002.74.3
Max model size (Q4)~13B comfortably~34B comfortably

The 3090 wins on pure value metrics. But value isn’t everything — warranty, power efficiency, and noise matter for a daily-use workstation.

My recommendation

If your budget is under $1,000 and you want maximum model flexibility, buy the used RTX 3090. The 24GB VRAM ceiling is simply more future-proof for LLM work. Models keep getting bigger, and VRAM is the one spec you can’t work around.

If you want a clean, new-card experience and only run 7B-13B models, the RTX 5070 Ti is the smarter pick. You get warranty coverage, lower power draw, and enough VRAM for the most popular open-weight models.

For more options in this price range, see the full best GPU for LLM under $1,000 roundup.

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Frequently asked questions

Can the RTX 5070 Ti run 34B models?

No. 34B models at Q4_K_M need ~20GB VRAM, which exceeds the 5070 Ti’s 16GB. You need a 24GB card like the RTX 3090 or RTX 4090.

Is a used RTX 3090 reliable for LLM inference?

Yes, if bought from a reputable seller. LLM inference is lighter on the GPU than mining or sustained gaming. Check for dead VRAM and test with a stress tool before committing.

Which is faster for 7B models, the 5070 Ti or 3090?

The 3090 edges it out at ~55 vs ~45 tok/s, but both are well above the interactive threshold. The 5070 Ti is more power-efficient.

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