Home / Models / Gemma 2 27B Instruct / NVIDIA RTX 5000 32 GB

Calculated memory fit · performance is a separate section

Can Gemma 2 27B Instruct run on NVIDIA RTX 5000 32 GB?

Yes. Calculated memory fit: Gemma 2 27B 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 27B Instruct · 27B
GPU
NVIDIA RTX 5000 32 GB · 32 GB advertised

What else can NVIDIA RTX 5000 32 GB run? · Find other GPUs for Gemma 2 27B Instruct

Memory calculation

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

Model weights16.0 GB
KV cache2.9 GB
Runtime reserve1.3 GB
Safety margin0.7 GB
Required (estimated)20.9 GB
GPU usable VRAM28.8 GB

Result: FITS IN VRAM

Quantization table

Quantization2K4K8K
BF16OffloadOffloadOffload
FP16OffloadOffloadOffload
Q3FitsFitsFits
Q4FitsFitsFits
Q5FitsFitsFits
Q6FitsFitsFits
Q8OffloadOffloadOffload

What fits entirely in VRAM?

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.

Check price on Amazon

HP

HP NVIDIA RTX 5000 Ada 32 GB 4DP Graphics

32 GB · Amazon unmatched

Check availability

Sources

Model: official config google/gemma-2-27b-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.