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Can I run this LLM?

Can a NVIDIA RTX 5060 Ti (16GB) run DeepSeek-R1-Distill 14B?

DeepSeek · Apache 2.0 · estimated for a 16.0 GB machine at 4K context.

Yes — it runs great.

Runs great

Best fit: DeepSeek-R1-Distill 14B at Q5_K_M · 10.5 GB weights · 27–41 tok/s on a NVIDIA RTX 5060 Ti (16GB).

Arena Text Overall · style-controlled

UnratedNo exact match

No reviewed exact Arena match

No reviewed exact model/configuration match in the Arena Text Overall style-controlled snapshot. No family or editorial score is substituted. Local quantization quality is unmeasured.

Snapshot published 2026-10-08 · snapshot imported 2026-10-11 UTC · validated last-good data · manual refresh

Arena leaderboard dataset · Arena / lmarena-ai, Arena Leaderboard Dataset (CC BY 4.0). Selected Text Overall style-controlled rows; field names adapted, ratings unchanged. · dataset CC BY 4.0 · revision e16f90232986

Total memory at 4K context
12.1 GB
Weights + KV cache + runtime overhead
Estimated generation
27–41 tok/s
Estimated first token
~7.7s

Every quantization on this machine

On small screens, each quant lists every metric below its name. On wider screens, scroll sideways for total memory, speed and fit. Keyboard: focus the table, then use the arrow keys. Quant names stay visible.

DeepSeek-R1-Distill 14B quantizations on NVIDIA RTX 5060 Ti (16GB), estimated at 4K context. Weights and total memory are shown separately.
QuantWeightsTotal memorySpeedFit
Q2_K5.8 GB7.4 GB44–66 tok/sRuns great
Q3_K_M7.3 GB8.9 GB37–55 tok/sRuns great
Q4_K_M9.0 GB10.6 GB31–46 tok/sRuns great
Q5_K_M10.5 GB12.1 GB27–41 tok/sRuns great
Q6_K12.1 GB13.7 GB24–36 tok/sTight / slow
Q8_015.7 GB17.3 GB— not residentWon't fit
FP1629.6 GB31.2 GB— not residentWon't fit

Ran DeepSeek-R1-Distill 14B on a NVIDIA RTX 5060 Ti (16GB)? Add your real numbers →