Can I Run Cogito v1 on NVIDIA GeForce RTX 5080?

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 29 września 2026

Yes, comfortably — Cogito v1 14B at Q4_K_M needs 10.9 GB at 8K context (8.5 GB weights + 2.4 GB KV cache/overhead), leaving ~5.1 GB of the NVIDIA GeForce RTX 5080's 16 GB, at ~74 tok/s (est.), with room for up to 32K context.

See what else this hardware can run →

Kup ten sprzęt NVIDIA GeForce RTX 5080 16GB — 16 GB VRAM · 360 W board powerUruchom w chmurze RTX 4090 w RunPod — od $0.34/godz. · stawka sprawdzona 2026-07

lub porównaj w Vast.ai od $0.35/godz. (typical low · varies)

Jako partner Amazon zarabiamy na kwalifikujących się zakupach. Linki do chmurowych GPU są linkami polecającymi — możemy otrzymać prowizję bez dodatkowych kosztów dla Ciebie.

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.

NVIDIA GeForce RTX 5080 16GB
16 GB VRAM · 360 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

NVIDIA GeForce RTX 5080 Specs

VRAM16 GB
Memory Bandwidth960 GB/s

Cogito v1 14B on the NVIDIA GeForce RTX 5080: VRAM by quantization

QuantVRAM neededFits 16 GB?Max contextWhole PC
F1630.4 GB✗ No——
Q8_017.3 GB✗ No——
Q6_K13.9 GB✓ Yes16K—
Q5_K_M12.3 GB✓ Yes16K—
Q4_K_M10.9 GB✓ Yes32K—
Q3_K_M8.4 GB✓ Yes32K—
Q2_K7 GB✓ Yes32K—

Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 16 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.

Context costs VRAM too. At Q4_K_M on the NVIDIA GeForce RTX 5080: 8K 10.9 GB · 32K 15.7 GB · 128K 35 GB ✗. Past 128K it no longer fits 16 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.

No compatible GPU? Cogito v1 14B on 16 GB of system RAM, CPU only: runs, but it is tight.

Cogito v1 Sizes That Fit the NVIDIA GeForce RTX 5080 (at 8K context)

Cogito v1 14BQ4_K_M · 10.9 GB at 8K context · ~74 tok/s (est.)
Cogito v1 8BQ4_K_M · 6.7 GB at 8K context · ~113 tok/s (est.)
Cogito v1 3BQ4_K_M · 3.6 GB at 8K context · ~198 tok/s (est.)
Buy vs. rent Cogito v1
Buy the GPU
~$999
NVIDIA GeForce RTX 5080 · MSRP
Rent by the hour
from $0.34/hr
RTX 4090 (24 GB) class

At 2 hrs/day, buying (~$999) beats renting at $0.34/hr after about 4.1 years.

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RunPod $0.34/hr
Rent on RunPod →
Vast.ai $0.35/hr · typical low · varies
Rent on Vast.ai →

Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.

FAQ

Can I run Cogito v1 on the NVIDIA GeForce RTX 5080?

Yes, comfortably — Cogito v1 14B at Q4_K_M needs 10.9 GB at 8K context (8.5 GB weights + 2.4 GB KV cache/overhead), leaving ~5.1 GB of the NVIDIA GeForce RTX 5080's 16 GB, at ~74 tok/s (est.), with room for up to 32K context.

What's the best Cogito v1 size for the NVIDIA GeForce RTX 5080?

Cogito v1 14B at Q4_K_M quantization needs 10.9 GB at 8K context (8.5 GB weights + 2.4 GB KV cache/overhead), estimated ~74 tokens/sec, up to 32K context.

Every Cogito v1 size on the NVIDIA GeForce RTX 5080

SizeVRAM at 8KVerdictSpeed
Cogito v1 70B45.7 GBDoes not fit—
Cogito v1 32B22.3 GBRuns at Q2_K—
Cogito v1 14B10.9 GBRuns~74 tok/s
Cogito v1 8B6.7 GBRuns~113 tok/s
Cogito v1 3B3.6 GBRuns~198 tok/s

Cogito v1 on Other GPUs

Popular Models on the NVIDIA GeForce RTX 5080

VRAM Tier

Troubleshooting

Buying Guide

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