Home / Models / Qwen2.5-Coder 32B Instruct / NVIDIA GTX 1080 Ti 11 GB

Calculated memory fit · not a benchmark

Can Qwen2.5-Coder 32B Instruct run on NVIDIA GTX 1080 Ti 11 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
Qwen2.5-Coder 32B Instruct · 33B
GPU
NVIDIA GTX 1080 Ti 11 GB · 11 GB advertised

Memory calculation

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

Model weights19.1 GB
KV cache2.0 GB
Runtime reserve1.5 GB
Safety margin0.8 GB
Required (estimated)23.3 GB
GPU usable VRAM9.9 GB

Result: CPU RAM OFFLOAD REQUIRED

Quantization table

Quantization2K4K8K16K32K
BF16NoNoNoNoNo
FP16NoNoNoNoNo
Q3OffloadOffloadOffloadOffloadOffload
Q4OffloadOffloadOffloadOffloadOffload
Q5OffloadOffloadOffloadOffloadOffload
Q6NoNoNoNoNo
Q8NoNoNoNoNo

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

MSI

MSI GAMING GTX 1080 Ti X 11G

11 GB · Amazon unmatched

Check availability
MSI

MSI GAMING GTX 1080 TI 11G

11 GB · Amazon unmatched

Check availability
MSI

MSI AERO GTX 1080 Ti 11G OC

11 GB · Amazon unmatched

Check availability
MSI

MSI ARMOR GTX 1080 Ti 11G OC

11 GB · Amazon unmatched

Check availability

Sources

Model: official config Qwen/Qwen2.5-Coder-32B-Instruct (main). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: DOES_NOT_FIT. Amazon: affiliate commerce match, not a spec source.