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Can I run this LLM?

Can a NVIDIA H200 (141GB) run Ornith 1.0 35B (MoE)?

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

Yes — it runs great.

Runs great

Best fit: Ornith 1.0 35B (MoE) at FP16 · 69.4 GB weights · 225–338 tok/s on a NVIDIA H200 (141GB).

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
70.3 GB
Weights + KV cache + runtime overhead
Estimated generation
225–338 tok/s
Estimated first token
~0.1s

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.

Ornith 1.0 35B (MoE) quantizations on NVIDIA H200 (141GB), estimated at 4K context. Weights and total memory are shown separately.
QuantWeightsTotal memorySpeedFit
Q2_K12.3 GB13.1 GB328–492 tok/sRuns great
Q3_K_M16.7 GB17.6 GB317–475 tok/sRuns great
Q4_K_M22.1 GB23.0 GB304–456 tok/sRuns great
Q5_K_M26.5 GB27.3 GB295–442 tok/sRuns great
Q6_K29.3 GB30.2 GB289–433 tok/sRuns great
Q8_036.9 GB37.8 GB274–411 tok/sRuns great
FP1669.4 GB70.3 GB225–338 tok/sRuns great
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