Can Gemma 2 9B Instruct run on NVIDIA RTX A1000 8 GB?

Yes. Calculated memory fit: Gemma 2 9B Instruct can run entirely in this GPU’s usable VRAM at one or more supported quantizations.

Can it run?

Can it run?: Yes, full GPU fit (calculated estimate).
Full GPU fit?: Yes
Model: Gemma 2 9B Instruct · 9.2B
GPU: NVIDIA RTX A1000 8 GB · 8 GB advertised

What else can NVIDIA RTX A1000 8 GB run? · Find other GPUs for Gemma 2 9B Instruct

Memory calculation

Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.

Model weights	5.4 GB
KV cache	2.6 GB
Runtime reserve	0.8 GB
Safety margin	0.4 GB
Required (estimated)	9.2 GB
GPU usable VRAM	7.2 GB

Result: CPU RAM OFFLOAD REQUIRED

Quantization table

Quantization	2K	4K	8K
BF16	Offload	Offload	Offload
FP16	Offload	Offload	Offload
Q3	Fits	Fits	Limited context
Q4	Offload	Offload	Offload
Q5	Offload	Offload	Offload
Q6	Offload	Offload	Offload
Q8	Offload	Offload	Offload

What fits entirely in VRAM?

Q3 at 2K context
Q3 at 4K context

What requires RAM offload?

Offload is shown only when the model does not fully fit in usable VRAM but stays within the modeled offload allowance.

Performance

No llama.cpp performance result is published for this pair yet. Memory fit above is unchanged. How performance is calculated

Available graphics cards

These SKUs use this GPU chip. Amazon CTAs appear only for EXACT/HIGH matches. Absence of a price does not change the compatibility result above.

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Lenovo

Lenovo 4X61Q73041 graphics card NVIDIA RTX A1000 8 GB GDDR6

8 GB · Amazon EXACT

$498.99

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HP NVIDIA RTX A1000 8 GB with Mini Bracket 4mDP Graphics

8 GB · Amazon EXACT

$834.00

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Sources

Model: official config google/gemma-2-9b-it (official-fallback-config). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: CPU_RAM_OFFLOAD_REQUIRED. Amazon: affiliate commerce match, not a spec source.