Can the RTX 4090 run a 70B model?

Not at q4. A 70B model at q4 needs roughly 40GB, beyond the 4090's 24GB, so it requires CPU offload and slows to a crawl. The 4090 is ideal for 7B–13B models and excellent for fine-tuning smaller models.

Is the RTX 4090 worth it for AI in 2026?

For the fastest single-card consumer inference and training of models up to 13B, yes. If you only need inference and care about cost, a used 24GB card like the 3090 offers similar VRAM for far less.

How much power does the RTX 4090 draw?

450W TDP with transient spikes toward 600W. Budget a 1000W PSU and good case airflow; it is the most power-hungry consumer GPU here.

NVIDIA Ada Lovelace 2022 flagship

NVIDIA GeForce RTX 4090

// 24 GB GDDR6X · 450W TDP · 82.6 TFLOPS FP32

▸ AI VALUE

4.0/5

FLAGSHIP · RANK #4.8

▸ VRAM

24GB

▸ FP32

82.6TFL

▸ FP16

82.6TFL

▸ MEM BW

1008GB/s

▸ TDP

450W

Buy · Check price ↗ + Compare ← All GPUs

LLM Inference Performance

// tokens/sec · q4 quantization · vLLM

Model	Tokens / sec	Local Fit
Mistral 7b Q4	150 tok/s	fits · single GPU
Llama 3 8b Q4	140 tok/s	fits · single GPU
Llama 3 13b Q4	78 tok/s	fits · single GPU
Llama 3 70b Q4	— OOM —	OOM / offload

Local Model Compatibility

// single-GPU · no CPU offload

7B params (int) fits

13B params fits

70B (4-bit quant) OOM

Spec Sheet

// verified · Ada Lovelace

▸ COMPUTEA0

▸ ARCHITECTURE Ada Lovelace

▸ GPU CHIP AD102

▸ CUDA CORES 16,384

▸ TENSOR CORES 512

▸ BOOST CLOCK 2520 MHz

▸ FP32 82.6 TFLOPS

▸ FP16 / BF16 82.6 TFLOPS

▸ LAUNCH YEAR 2022

▸ MEMORY & RATINGSB0

▸ VRAM 24 GB GDDR6X

▸ BANDWIDTH 1008 GB/s

▸ TIER flagship

▸ OVERALL 4.8/5

▸ AI VALUE 4.0/5

▸ GAMING VALUE 4.2/5

▸ POWERC0

▸ TDP 450 W

▸ PERF/W (FP32) 0.184 TFL/W

▸ MODEL FITD0

▸ RUNS 7B (INT) yes

▸ RUNS 13B yes

▸ RUNS 70B (4-bit) no

▸ PLATFORM CUDA · ROCm via HIP

Comparable GPUs

// head-to-head comparisons

rtx 3090

The 3090 has the same 24GB VRAM for far less on the used market; the 4090 is roughly 2x faster and adds Ada efficiency for those who need speed.

Compare ▸

rx 7900 xtx

The 7900 XTX matches VRAM and wins on gaming value, but CUDA still dominates AI tooling, so the 4090 is the safer AI pick.

Compare ▸

Analysis notes

Quick Summary

For RTX 4090 AI work in 2026, this is still the fastest single consumer card you can buy. With 16,384 CUDA cores, 512 fourth-gen Tensor cores, 24GB of GDDR6X and 82.6 TFLOPS of FP32, it chews through local LLM inference up to 13B parameters and handles fine-tuning that lesser cards can’t. The catches are a 450W appetite and a flagship price.

Specs That Matter for AI

The 24GB VRAM is the headline — it sets the ceiling on model size. The 4090 comfortably runs 7B and 13B models quantized, but a 70B model at q4 (~40GB) exceeds its memory and forces slow CPU offload. Memory bandwidth of ~1 TB/s keeps token generation fast where the model fits.

Performance

Expect ~140 tok/s on Llama 3 8B q4 and ~78 tok/s on 13B q4 — the quickest in this database. For training and LoRA fine-tuning of smaller models, the Tensor cores and bandwidth make it the clear leader among consumer hardware.

Verdict

If you want maximum consumer AI speed and can absorb the power and price, the 4090 is unmatched. If your workload is inference-only and VRAM-bound, a cheaper 24GB card delivers most of the capability for far less money.

Frequently Asked Questions

Can the RTX 4090 run a 70B model?: Not at q4. A 70B model at q4 needs roughly 40GB, beyond the 4090's 24GB, so it requires CPU offload and slows to a crawl. The 4090 is ideal for 7B–13B models and excellent for fine-tuning smaller models.
Is the RTX 4090 worth it for AI in 2026?: For the fastest single-card consumer inference and training of models up to 13B, yes. If you only need inference and care about cost, a used 24GB card like the 3090 offers similar VRAM for far less.
How much power does the RTX 4090 draw?: 450W TDP with transient spikes toward 600W. Budget a 1000W PSU and good case airflow; it is the most power-hungry consumer GPU here.