# Ornith 1.0 35B: RAM and VRAM requirements

> Ornith 1.0 35B is a 35B Ornith model (Mixture-of-Experts, 3B active per token). At Q4_K_M it needs about **23.2 GB** to run and fits **9 of 40** tracked devices. Minimum to run: Nvidia GeForce RTX 5090 (32GB).

Last validated: 2026-08-03. Sources: Ollama, HuggingFace GGUF repos, vendor specs.

## Memory by quantization
| Quant | On disk | To run (4k context) |
| --- | --- | --- |
| Q4_K_M | 21 GB | ~23.2 GB |
| Q8_0 | 37 GB | ~39.2 GB |
| FP16 | 69 GB | ~71.2 GB |

Memory = weights + KV cache + ~0.8 GB runtime overhead, and varies ±15% with context length.

## Will it run on my device?
- **Apple M1 (8GB)** (8 GB): No, not enough memory
- **iPhone 17** (8 GB): No, not enough memory
- **iPhone 17 Pro** (12 GB): No, not enough memory
- **16GB RAM Laptop (CPU/iGPU only)** (16 GB): No, not enough memory
- **Google Pixel 10 Pro** (16 GB): No, not enough memory
- **Nvidia GeForce RTX 3090 (24GB)** (24 GB): No, not enough memory
- **Apple M4 Pro (48GB)** (48 GB): Yes, it runs
- **Apple M3 Ultra (256GB)** (256 GB): Yes, it runs (room for FP16)

Full table of all 40 devices: https://localmodel.run/model/ornith-1.0-35b

## How to run
Quickest path: `ollama run ornith:35b`. On Mac, LM Studio (ships MLX) is fastest; on Linux, Ollama for chat or vLLM to serve; on Windows, LM Studio or Ollama.

## Details
- Parameters: 35B (MoE, 3B active per token)
- Default context: 256k tokens
- License: MIT (commercial use: yes)
- Released: 2026-06
- HuggingFace: 2,797,174 downloads/mo, 462 likes

## FAQ
### How much VRAM or RAM does Ornith 1.0 35B need?
About 23.2 GB at Q4_K_M (weights 21 GB + KV cache + overhead) at a 4k context. Budget ~39.2 GB for Q8_0.
### Can Ornith 1.0 35B run on a laptop?
Ornith 1.0 35B is large; you need a high-memory Mac or a 24 GB+ GPU at Q4_K_M.
### Can I use Ornith 1.0 35B commercially?
Yes, MIT permits commercial use.

Sources: https://huggingface.co/deepreinforce-ai/Ornith-1.0-35B, https://huggingface.co/deepreinforce-ai/Ornith-1.0-35B-GGUF, https://ollama.com/library/ornith/tags, https://deep-reinforce.com/ornith.html
More: https://localmodel.run/model/ornith-1.0-35b