How fast does Gemma 4 26B-A4B run on the NVIDIA RTX 3090 Ti?

Gemma 4 26B-A4B runs at about 138 tokens/s on the NVIDIA RTX 3090 Ti (measured, Q4_K_M, CUDA, llama-bench). Based on 1 measured run(s), each linked to its public source.

Does Gemma 4 26B-A4B Q4_K_M fit in the NVIDIA RTX 3090 Ti's memory?

Estimate: the Q4_K_M file is 16.8 GB and needs about 18.2 GB with an ~8K context; the NVIDIA RTX 3090 Ti has about 23.5 GB usable, so it fits.

Gemma 4 26B-A4B › NVIDIA RTX 3090 Ti

Gemma 4 26B-A4B on the NVIDIA RTX 3090 Ti

Gemma 4 26B-A4B runs at about 138 tokens/s on the NVIDIA RTX 3090 Ti (measured, Q4_K_M, CUDA, llama-bench).

Best measured: 138 tokens/s generation and 4,184 tokens/s prompt processing (Q4_K_M, CUDA).

For comparison, our size-scaling estimate for this combination is 128 tok/s.

Every run

Quant	Backend	Generate tok/s	Prompt tok/s	Test	Build / by / notes	Source
Q4_K_M	CUDA	138	4,184	tg64	Comparison run in a stock container, same article.	Algol Labs Gemma 4 benchmark

tg128 = generating 128 tokens; pp512 = reading a 512-token prompt (llama-bench). LocalScore averages several prompt and output lengths, so its numbers run lower than tg128. "decode, llama-server" = single-stream generation speed measured against a running llama-server (no speculative decoding).

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