Q: What quantization of Gemma 3 27B should I use on a NVIDIA GeForce GTX 1070 Ti?

For 8 GB VRAM on the NVIDIA GeForce GTX 1070 Ti, the Q8_0 variant is the best fit. Estimated ~3 tokens/sec on the Q8_0 quantization.

Q: How fast does Gemma 3 27B run on NVIDIA GeForce GTX 1070 Ti?

Roughly 3 tokens/sec for Q8_0. Real speed depends on context length, backend (Ollama, llama.cpp, LM Studio), and KV cache size.

Q: What if NVIDIA GeForce GTX 1070 Ti is not enough for Gemma 3 27B?

Consider upgrading to Apple M3 Pro (36 GB VRAM) which fits the recommended 36 GB target. Or pick a smaller quantization to stay on your current card.

Question 1

Can I run Gemma 3 27B on a NVIDIA GeForce GTX 1070 Ti?

Accepted Answer

Sort of — NVIDIA GeForce GTX 1070 Ti can run Gemma 3 27B (Q8_0) only by spilling layers to RAM. Generation will be slow. CPU + GPU hybrid — not enough VRAM (8 GB < 30 GB min), but 64 GB RAM is sufficient. Expect significantly slower inference.

Question 2

What quantization of Gemma 3 27B should I use on a NVIDIA GeForce GTX 1070 Ti?

Accepted Answer

For 8 GB VRAM on the NVIDIA GeForce GTX 1070 Ti, the Q8_0 variant is the best fit. Estimated ~3 tokens/sec on the Q8_0 quantization.

Question 3

How fast does Gemma 3 27B run on NVIDIA GeForce GTX 1070 Ti?

Accepted Answer

Roughly 3 tokens/sec for Q8_0. Real speed depends on context length, backend (Ollama, llama.cpp, LM Studio), and KV cache size.

Question 4

What if NVIDIA GeForce GTX 1070 Ti is not enough for Gemma 3 27B?

Accepted Answer

Consider upgrading to Apple M3 Pro (36 GB VRAM) which fits the recommended 36 GB target. Or pick a smaller quantization to stay on your current card.

Quantization	File Size	Min VRAM	Rec VRAM	Context	Verdict	Estimated tok/s
Q4_K_M	16 GB	18 GB	24 GB	8K / 32K	Hybrid CPU+GPU	~5
Q8_0Best fit	28.7 GB	30 GB	36 GB	8K / 32K	Hybrid CPU+GPU	~3

Can I Run Gemma 3 27B on NVIDIA GeForce GTX 1070 Ti?

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Every Gemma 3 27B quantization on NVIDIA GeForce GTX 1070 Ti

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