Home / Models / Qwen2.5 14B Instruct / NVIDIA RTX A1000 8 GB

Calculated memory fit · performance is a separate section

Can Qwen2.5 14B Instruct run on NVIDIA RTX A1000 8 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 14B Instruct · 15B
GPU
NVIDIA RTX A1000 8 GB · 8 GB advertised

What else can NVIDIA RTX A1000 8 GB run? · Find other GPUs for Qwen2.5 14B Instruct · See 2× multi-GPU options

Memory calculation

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

Model weights8.6 GB
KV cache1.5 GB
Runtime reserve0.9 GB
Safety margin0.5 GB
Required (estimated)11.6 GB
GPU usable VRAM7.2 GB

Result: CPU RAM OFFLOAD REQUIRED

Quantization table

Quantization2K4K8K16K32K
BF16NoNoNoNoNo
FP16NoNoNoNoNo
Q3OffloadOffloadOffloadOffloadOffload
Q4OffloadOffloadOffloadOffloadOffload
Q5OffloadOffloadOffloadOffloadOffload
Q6OffloadOffloadOffloadOffloadOffload
Q8OffloadOffloadOffloadOffloadOffload

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. Performance numbers below are only published for full-VRAM fits.

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

Sources

Model: official config Qwen/Qwen2.5-14B-Instruct (main). 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.