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Ornith · 397B parameters · chat, reasoning, coding, vision.
Ollama weight files: Default 242 GB (ornith-1.5:397b).
Yes on 5 machines in this list. The smallest is 4x Mac Studio M5 Max (40c GPU) 128GB: Q5_K_M, about 290.4 GB, roughly 1 tokens per second, via llama.cpp. llama-server -hf ornith-ai/Ornith-1.5-397B-GGUF:Q5_K_M --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node
llama-server -hf ornith-ai/Ornith-1.5-397B-GGUF:Q5_K_M --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node| Hardware | Runtime | Quant | Memory | Fit | Speed | Command |
|---|---|---|---|---|---|---|
| 4x Mac Studio M5 Max (40c GPU) 128GB | llama.cpp | Q5_K_M GGUF | 290.4 GB | fits in fast memory | ~1 tok/s | llama-server -hf ornith-ai/Ornith-1.5-397B-GGUF:Q5_K_M --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node |
| 2x Mac Studio M5 Ultra (80c GPU) 256GB | llama.cpp | Q5_K_M GGUF | 290.4 GB | fits in fast memory | ~3 tok/s | llama-server -hf ornith-ai/Ornith-1.5-397B-GGUF:Q5_K_M --rpc node2:50052 -c 8192 # run rpc-server on each other node |
| Mac Studio M3 Ultra (80c GPU) 512GB | Ollama | Default | 246.1 GB | fits in fast memory | ~3 tok/s | ollama run ornith-1.5:397b |
| 4x DGX Spark 128GB | llama.cpp | Q5_K_M GGUF | 290.4 GB | fits in fast memory | ~1 tok/s | llama-server -hf ornith-ai/Ornith-1.5-397B-GGUF:Q5_K_M --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node |
| 4x Mac Studio M5 Ultra (80c GPU) 256GB | llama.cpp | Q8_0 GGUF | 432.6 GB | fits in fast memory | ~2 tok/s | llama-server -hf ornith-ai/Ornith-1.5-397B-GGUF:Q8_0 --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node |
Estimates, not benchmarks. Model sizes are ollama.com download sizes; memory needed adds headroom for ~8k tokens of context; speeds are rough figures from memory bandwidth. Data updated 2026-10-16.
A project by OnDevice Labs · llms.txt