Can I Run Cosmos 3 on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM)?

Written by Jakub Rusinowski · Last updated July 21, 2026

Yes, but it is tight

Yes, but it is tight — Cosmos 3 Nano at Q6_K needs about 15.4 GB of the 16 GB usable on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM), leaving only ~0.6 GB before the runtime starts swapping. Expect ~80.9 tok/s (estimated), with room for about 8,192 tokens of context.

Confidence: low · Recommended quantization: Q6_K · Estimated speed: ~80.9 tok/s

RTX 5080 Desktop (16 GB VRAM, 32 GB RAM) — what it gives a model

Usable memory for models16 GB
Memory bandwidth960 GB/s
Form factorDesktop
Operating systemWindows or Linux
Memory upgradeableYes

Cosmos 3 on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM): memory by quantization

QuantMemory neededFits 16 GB?Max contextEst. speedDownload
F1634.2 GB✗ No32 GB
Q8_019.2 GB✗ No17 GB
Q6_K15.4 GB✓ Yes8K~80.9 tok/s13.1 GB
Q5_K_M13.6 GB✓ Yes16K~89.9 tok/s11.3 GB
Q4_K_M11.9 GB✓ Yes16K~100.4 tok/s9.7 GB
Q3_K_M9.1 GB✓ Yes16K~125.2 tok/s6.8 GB
Q2_K7.5 GB✓ Yes16K~144.9 tok/s5.3 GB

Which Cosmos 3 sizes fit

VariantNeeds at Q4_K_MFits?Est. speed
Cosmos 3 Super41.8 GB✗ Too large
Cosmos 3 Nano11.9 GB✓ Fits~100.4 tok/s
Cosmos 3 Edge4.1 GB✓ Fits~219.7 tok/s

What to watch out for

RTX 5080 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 Cosmos 3 on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM)?

Yes, but it is tight — Cosmos 3 Nano at Q6_K needs about 15.4 GB of the 16 GB usable on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM), leaving only ~0.6 GB before the runtime starts swapping. Expect ~80.9 tok/s (estimated), with room for about 8,192 tokens of context.

Which quantization of Cosmos 3 should I use on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM)?

Q6_K — it needs about 15.4 GB of the 16 GB available, downloads as roughly 13.1 GB, and runs at an estimated 80.9 tokens/sec with up to 8K of context.

What limits Cosmos 3 on RTX 5080 Desktop (16 GB VRAM, 32 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 5080 Desktop (16 GB VRAM, 32 GB RAM)

Cosmos 3 on GPUs

What This Model Is Good At

Model & Tools

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