Can the Radeon RX 7900 XTX run Llama 3.3 70B?

No. Llama 3.3 70B needs about 41.8 GB at Q4_K_M (weights plus 1.8 GB runtime overhead), and the Radeon RX 7900 XTX has 24 GB, so it won't fit without offloading layers to system RAM, which is far slower.

VRAM
24 GB
Needs at Q4
41.8 GB
Short by
17.8 GB
Speed
-

Every quantization

Llama 3.3 70B (70B) on 24 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M40 GB41.8 GBToo big -
Q5_K_M48 GB49.8 GBToo big -
Q8_075 GB76.8 GBToo big -
FP16140 GB141.8 GBToo big -

Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the Radeon RX 7900 XTX's 960 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.

What to do instead

Two ways forward

Cheapest cards that run it

Models that fit the Radeon RX 7900 XTX

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Same model, other hardware - and other models on this card

Llama 3.3 70B on other hardware

Also runs on the Radeon RX 7900 XTX

Frequently asked

Quick answers

Can the AMD Radeon RX 7900 XTX run Llama 3.3 70B?

No. Llama 3.3 70B needs about 41.8 GB at Q4_K_M (weights plus 1.8 GB runtime overhead), and the Radeon RX 7900 XTX has 24 GB, so it won't fit without offloading layers to system RAM, which is far slower.

How much VRAM does Llama 3.3 70B need?

About 40 GB of weights at Q4_K_M, 75 GB at Q8_0 and 140 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Llama 3.3 70B on the Radeon RX 7900 XTX?

It doesn't fit in the Radeon RX 7900 XTX's memory, so speed depends on how many layers you offload to system RAM - typically single-digit tokens per second or lower.