Can I Run Falcon 3 on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM)?

Written by Jakub Rusinowski · Last updated December 18, 2024

Yes — comfortably

Yes, comfortably — Falcon 3 10B Instruct at Q8_0 needs about 13.1 GB of the 24 GB usable on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM), leaving ~10.9 GB spare and running at ~53.2 tok/s (estimated), with room for about 32,768 tokens of context.

Confidence: high · Recommended quantization: Q8_0 · Estimated speed: ~53.2 tok/s

RTX 3090 Desktop (24 GB VRAM, 64 GB RAM) — what it gives a model

Usable memory for models24 GB
Memory bandwidth936 GB/s
Form factorDesktop
Operating systemWindows or Linux
Memory upgradeableYes

Falcon 3 on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM): memory by quantization

QuantMemory neededFits 24 GB?Max contextEst. speedDownload
F1622.7 GB✓ Yes8K~30.7 tok/s20.6 GB
Q8_013.1 GB✓ Yes32K~53.2 tok/s10.9 GB
Q6_K10.6 GB✓ Yes32K~65.6 tok/s8.4 GB
Q5_K_M9.4 GB✓ Yes32K~73.5 tok/s7.3 GB
Q4_K_M8.4 GB✓ Yes32K~82.9 tok/s6.2 GB
Q3_K_M6.5 GB✓ Yes32K~105.8 tok/s4.4 GB
Q2_K5.5 GB✓ Yes32K~124.6 tok/s3.4 GB

Which Falcon 3 sizes fit

VariantNeeds at Q4_K_MFits?Est. speed
Falcon 3 10B Instruct8.4 GB✓ Fits~82.9 tok/s
Falcon 3 7B Instruct6.2 GB✓ Fits~107.2 tok/s
Falcon 3 3B Instruct3.5 GB✓ Fits~180.2 tok/s

RTX 3090 desktop limitations

Recommended setup

Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving

How these numbers are calculated

FAQ

Can I run Falcon 3 on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM)?

Yes, comfortably — Falcon 3 10B Instruct at Q8_0 needs about 13.1 GB of the 24 GB usable on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM), leaving ~10.9 GB spare and running at ~53.2 tok/s (estimated), with room for about 32,768 tokens of context.

Which quantization of Falcon 3 should I use on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM)?

Q8_0 — it needs about 13.1 GB of the 24 GB available, downloads as roughly 10.9 GB, and runs at an estimated 53.2 tokens/sec with up to 32K of context.

What limits Falcon 3 on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM)?

Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.

Which runtime should I use?

Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving

Other Computers

Other Models on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM)

Falcon 3 on GPUs

What This Model Is Good At

Model & Tools

← Can I Run It? | Falcon 3 model page | Check your hardware