Can I Run Cogito v1 on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM)?

Written by Jakub Rusinowski · Last updated March 20, 2026

Yes

Yes — Cogito v1 14B at Q6_K needs about 13.9 GB of the 16 GB usable on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM) (~2.1 GB spare), at ~51.8 tok/s (estimated), with room for about 16,384 tokens of context.

Confidence: high · Recommended quantization: Q6_K · Estimated speed: ~51.8 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

Cogito v1 on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM): memory by quantization

QuantMemory neededFits 16 GB?Max contextEst. speedDownload
F1630.4 GB✗ No28 GB
Q8_017.3 GB✗ No14.9 GB
Q6_K13.9 GB✓ Yes16K~51.8 tok/s11.5 GB
Q5_K_M12.3 GB✓ Yes16K~58.3 tok/s9.9 GB
Q4_K_M10.9 GB✓ Yes32K~66.2 tok/s8.5 GB
Q3_K_M8.4 GB✓ Yes32K~85.8 tok/s6 GB
Q2_K7 GB✓ Yes32K~102.5 tok/s4.6 GB

Which Cogito v1 sizes fit

VariantNeeds at Q4_K_MFits?Est. speed
Cogito v1 70B45.7 GB✗ Too large
Cogito v1 32B22.3 GB✗ Too large
Cogito v1 14B10.9 GB✓ Fits~66.2 tok/s
Cogito v1 8B6.7 GB✓ Fits~103.1 tok/s
Cogito v1 3B3.6 GB✓ Fits~184.7 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 Cogito v1 on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM)?

Yes — Cogito v1 14B at Q6_K needs about 13.9 GB of the 16 GB usable on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM) (~2.1 GB spare), at ~51.8 tok/s (estimated), with room for about 16,384 tokens of context.

Which quantization of Cogito v1 should I use on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM)?

Q6_K — it needs about 13.9 GB of the 16 GB available, downloads as roughly 11.5 GB, and runs at an estimated 51.8 tokens/sec with up to 16K of context.

What limits Cogito v1 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)

Cogito v1 on GPUs

What This Model Is Good At

Model & Tools

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