Name: RX 7900 XTX
Brand: AMD

Question 1

What AI models can run on RX 7900 XTX?

Accepted Answer

The RX 7900 XTX (24 GB VRAM) can run models including recurrentgemma-9b, MediPhi-Instruct, Llama-2-7b-chat, Llama-3.2-1B-Instruct-QLORA_INT4_EO8, Llama-3.2-1B-Instruct-SpinQuant_INT4_EO8 and more — 10 compatible models indexed so far. Compatible models are determined by whether the model's memory footprint fits within the GPU's 24 GB VRAM, potentially using quantization (Q8, Q6, or Q4) to reduce memory usage.

Question 2

What is the cheapest cloud option for RX 7900 XTX?

Accepted Answer

We don't currently have cloud pricing data for the RX 7900 XTX. This GPU may not be widely available from major cloud providers, or pricing data hasn't been synced yet.

Question 3

Is RX 7900 XTX good for fine-tuning?

Accepted Answer

The RX 7900 XTX can handle fine-tuning with some constraints. With 24 GB of VRAM, it's suitable for LoRA/QLoRA fine-tuning of models up to ~7B parameters. Full fine-tuning is limited to smaller models (~1-3B parameters). Techniques like gradient checkpointing and mixed precision help maximize what fits.

Question 4

How much VRAM does RX 7900 XTX have?

Accepted Answer

The RX 7900 XTX has 24 GB of VRAM (GDDR6). It also offers 960 GB/s memory bandwidth, 122.8 TFLOPS of FP16 compute.

Question 5

What quantization formats work on RX 7900 XTX?

Accepted Answer

The RX 7900 XTX supports the following quantization formats: FP16 (full precision), Q8 (8-bit), Q6 (6-bit), Q4 (4-bit). FP16 works for models up to ~7B parameters. Q4 quantization lets models up to ~81B parameters (by VRAM estimate) fit on the RX 7900 XTX.

RX 7900 XTX

Specifications

Cloud pricing

Compatible models

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Frequently asked questions

VRAM	24 GB
Memory type	GDDR6
Bandwidth	960 GB/s
FP16 TFLOPS	122.8
FP8 support	No