Ornith-1.0-35B: hardware requirements
Ornith-1.0-35B needs about 24 GB of memory at Q4 quantization — a 21 GB download plus room for context and overhead. That fits a machine with 32GB RAM.
This is a mixture-of-experts model. Only a fraction of its 35B parameters are used for each token, so it runs faster than its size suggests — but all of it still has to fit in memory. The speed is that of a small model; the memory requirement is that of a large one. More on this →
Will it run on your machine?
Download sizes by quantization
Lower quantization means a smaller file and less memory, at some cost to quality. Q4_K_M is the usual starting point. What is this?
| Quant | Download | RAM @ 4K | RAM @ 32K | Source |
|---|---|---|---|---|
| Q4_K_Mrecommended | 21 GB | 24 GB | 26 GB | measured |
| Q5_K_M | 25 GB | 28 GB | 30 GB | measured |
| Q6_K | 29 GB | 32 GB | 34 GB | measured |
| Q8_0 | 37 GB | 40 GB | 43 GB | measured |
| BF16 | 69 GB | 73 GB | 75 GB | measured |
“Measured” sizes are read from published GGUF files (ornith-ai/Ornith-1.0-35B-GGUF). “Estimated” sizes are derived from the parameter count and are typically within a few percent. The RAM columns add the context cache and runtime overhead to the download size.