Can I run this LLM?
Can a NVIDIA H200 (141GB) run Ornith 1.5 9B?
Ornith · MIT · estimated for a 141.0 GB machine at 4K context.
Yes — it runs great.
Runs greatBest fit: Ornith 1.5 9B at FP16 · 17.9 GB weights · 128–192 tok/s on a NVIDIA H200 (141GB).
Arena Text Overall · style-controlled
UnratedNo exact matchNo 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
- 18.9 GB
- Weights + KV cache + runtime overhead
- Estimated generation
- 128–192 tok/s
- Estimated first token
- ~0.4s
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.
| Quant | Weights | Total memory | Speed | Fit |
|---|---|---|---|---|
| Q2_K | 4.1 GB | 5.0 GB | 256–384 tok/s | Runs great |
| Q3_K_M | 4.9 GB | 5.9 GB | 241–361 tok/s | Runs great |
| Q4_K_M | 5.9 GB | 6.8 GB | 226–339 tok/s | Runs great |
| Q5_K_M | 6.9 GB | 7.8 GB | 213–319 tok/s | Runs great |
| Q6_K | 7.7 GB | 8.6 GB | 203–304 tok/s | Runs great |
| Q8_0 | 9.6 GB | 10.5 GB | 183–275 tok/s | Runs great |
| FP16 | 17.9 GB | 18.9 GB | 128–192 tok/s | Runs great |
Ran Ornith 1.5 9B on a NVIDIA H200 (141GB)? Add your real numbers →