Can I run it?

Can I run Qwen2.5 7B Instruct on GeForce RTX 5090?

Runs great

Runs great fully on your GeForce RTX 5090 at F16, 8K context, about 63–86 tok/s. Weights 14.2 GB plus 0.44 GB of KV cache — 15.1 GB of 29.9 GB usable. Up to 32K context still fits.

Qwen2.5 7B Instruct details · GeForce RTX 5090 page · How this estimate is made

Run commands

llama-server -hf bartowski/Qwen2.5-7B-Instruct-GGUF:F16 -c 8192 -ngl 28

ollama run qwen2.5

lms get bartowski/Qwen2.5-7B-Instruct-GGUF
# Then load quant F16

Assumptions

• Estimate, not a benchmark. Decode speed uses a memory-bandwidth model at 55–75% of peak.
• KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
• F16 size is the real GGUF file size from Hugging Face.
• 0.5 GB is reserved because this GPU also drives a display, then 5% of the rest is left free.
• Speed is quoted at 8K context, not at the maximum context that still fits.

Larger models that also fit

• Can I run Qwen3.8 27B on GeForce RTX 5090? — Tight fit, UD-Q8_K_L, 34–47 tok/s
• Can I run gemma 4 12b it on GeForce RTX 5090? — Runs, BF16, 36–50 tok/s
• Can I run Qwen3.5 9B on GeForce RTX 5090? — Runs great, BF16, 54–74 tok/s

Updated 2026-10-17. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.