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Can I run this LLM?

Can a NVIDIA H200 (141GB) run Phi-4 14B?

Phi · MIT · estimated for a 141.0 GB machine at 4K context.

Yes — it runs great.

Runs great

Best fit: Phi-4 14B at FP16 · 29.3 GB weights · 89–134 tok/s on a NVIDIA H200 (141GB).

Arena Text Overall · style-controlled

1,256FP16 untested

phi-4 · published configuration reference · FP16 not tested

Arena Text Overall (style-controlled), exact published entry phi-4, 2026-10-08: reference rating 1,256.3. Published confidence bounds 1,251.7–1,260.9. 24,126 votes. Published phi-4 configuration reference. Reasoning mode is not disclosed by the Arena dataset. Tested precision, runtime and sampling settings are not disclosed in this dataset. Selected FP16 has not been measured by this Arena entry. No quantization quality adjustment is applied.

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
31.0 GB
Weights + KV cache + runtime overhead
Estimated generation
89–134 tok/s
Estimated first token
~0.7s

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.

Phi-4 14B quantizations on NVIDIA H200 (141GB), estimated at 4K context. Weights and total memory are shown separately.
QuantWeightsTotal memorySpeedFit
Q2_K5.6 GB7.2 GB220–330 tok/sRuns great
Q3_K_M7.2 GB8.8 GB200–301 tok/sRuns great
Q4_K_M8.9 GB10.5 GB183–274 tok/sRuns great
Q5_K_M10.4 GB12.0 GB170–254 tok/sRuns great
Q6_K12.0 GB13.7 GB157–236 tok/sRuns great
Q8_015.6 GB17.2 GB136–204 tok/sRuns great
FP1629.3 GB31.0 GB89–134 tok/sRuns great

Ran Phi-4 14B on a NVIDIA H200 (141GB)? Add your real numbers →