Home / Models / Gemma 2 27B Instruct / NVIDIA RTX 5070 Ti 16 GB

Calculated memory fit · not a benchmark

Can Gemma 2 27B Instruct run on NVIDIA RTX 5070 Ti 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 5070 Ti 16 GB · 16 GB advertised

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 VRAM14.4 GB

Result: CPU RAM OFFLOAD REQUIRED

Quantization table

Quantization2K4K8K
BF16NoNoNo
FP16NoNoNo
Q3OffloadOffloadOffload
Q4OffloadOffloadOffload
Q5OffloadOffloadOffload
Q6OffloadOffloadOffload
Q8OffloadOffloadOffload

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.

Check price on Amazon

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.