Home / Models / Gemma 2 27B Instruct / NVIDIA RTX 5000 16 GB
Can Gemma 2 27B Instruct run on NVIDIA RTX 5000 16 GB?
Can it run? Yes, with CPU/RAM offload. Full GPU fit? No.
Can it run?
- Can it run?
- Yes, with CPU/RAM offload. This is not equivalent to full-GPU inference.
- Full GPU fit?
- No
- Model
- Gemma 2 27B Instruct · 27B
- GPU
- NVIDIA RTX 5000 16 GB · 16 GB advertised
Memory calculation
Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.
| Model weights | 16.0 GB |
|---|---|
| KV cache | 2.9 GB |
| Runtime reserve | 1.3 GB |
| Safety margin | 0.7 GB |
| Required (estimated) | 20.9 GB |
| GPU usable VRAM | 14.4 GB |
Result: CPU RAM OFFLOAD REQUIRED
Quantization table
| Quantization | 2K | 4K | 8K |
|---|---|---|---|
| BF16 | No | No | No |
| FP16 | No | No | No |
| Q3 | Offload | Offload | Offload |
| Q4 | Offload | Offload | Offload |
| Q5 | Offload | Offload | Offload |
| Q6 | Offload | Offload | Offload |
| Q8 | Offload | Offload | Offload |
What fits entirely in VRAM?
No calculated full-VRAM fit at the evaluated quantizations and context lengths.
What requires RAM offload?
Weights may run with CPU/RAM offload. That is not equivalent to full-GPU inference. RigForAI does not estimate tokens/sec in this release.
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.
HP 5JH81AA graphics card NVIDIA Quadro RTX 5000 16 GB GDDR6
16 GB · Amazon EXACT
$602.99
Check price on Amazon
Fujitsu S26361-F2222-L505 graphics card NVIDIA Quadro RTX 5000 16 GB GDDR6
16 GB · Amazon unmatched
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.