Can the Radeon RX 7900 XTX run Gemma 4 26B A4B?

Yes. Gemma 4 26B A4B fits the Radeon RX 7900 XTX's 24 GB at Q4_K_M (about 16.8 GB needed), running at an estimated 162 tok/s. There's room for up to Q5_K_M if you want higher quality.

VRAM
24 GB
Needs at Q4
16.8 GB
Headroom
7.2 GB
Speed (Q4_K_M)
~162 tok/s

Every quantization

Gemma 4 26B A4B (26.5B, 4B active) on 24 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M15 GB16.8 GBFits~162 tok/s
Q5_K_M19 GB20.8 GBTight~128 tok/s
Q8_028 GB29.8 GBToo big -
FP1653 GB54.8 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.

Run it

Copy, paste, go

llama-server -hf google/gemma-4-26B-A4B-it-qat-q4_0-gguf -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Gemma 4 26B A4B details →

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

Gemma 4 26B A4B on other hardware

Also runs on the Radeon RX 7900 XTX

Frequently asked

Quick answers

Can the AMD Radeon RX 7900 XTX run Gemma 4 26B A4B?

Yes. Gemma 4 26B A4B fits the Radeon RX 7900 XTX's 24 GB at Q4_K_M (about 16.8 GB needed), running at an estimated 162 tok/s. There's room for up to Q5_K_M if you want higher quality.

How much VRAM does Gemma 4 26B A4B need?

About 15 GB of weights at Q4_K_M, 28 GB at Q8_0 and 53 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Gemma 4 26B A4B on the Radeon RX 7900 XTX?

Roughly 162 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the Radeon RX 7900 XTX's 960 GB/s memory bandwidth; as a mixture-of-experts model only about 4B parameters are read per token, which is why it is faster than its size suggests.