---
type: reference
title: Ornith Model Specifications
description: Specifications for Ornith-1.0-9B dense and Ornith-1.0-35B MoE models — context length, quantization options, memory requirements.
tags:
  - ornith
  - models
  - llama.cpp
  - GGUF
  - unverified
verified: 2026-08-28
---

# Model Specifications

## Ornith-1.0-9B-GGUF

- **Source:** https://huggingface.co/ornith-ai/Ornith-1.0-9B-GGUF
- **Architecture:** Dense ~9B model
- **Context Length:** 262,144 tokens (256K)
- **Quantization Options:**
  - Q4_K_M: 5.3 GB (recommended for most systems)
  - Q5_K_M: 6.47 GB
  - Q6_K: 7.36 GB
  - Q8_0: 9.53 GB
  - bf16: 17.9 GB

## Ornith-1.0-35B-GGUF (MoE)

- **Source:** https://huggingface.co/ornith-ai/Ornith-1.0-35B-GGUF
- **Architecture:** 35B MoE (Mixture of Experts)
- **Context Length:** 262,144 tokens (256K)
- **Quantization Options:**
  - Q4_K_M: 20 GB (recommended)
  - Other quantizations available

**Note:** No fp4 quantization exists for these models. Q4_K_M is the lightest quantization.

## Comparison: 9B vs 35B MoE

| Aspect | 9B Dense | 35B MoE |
|--------|----------|---------|
| **Memory (Q4)** | 5.3 GB | 20 GB |
| **VRAM for Full GPU** | 8 GB | 24-40 GB |
| **Speed (GPU)** | Faster | Slower but better quality |
| **Quality** | Good | Excellent |
| **Context** | 256K | 256K |
| **Best For** | Quick tasks, limited RAM | Complex reasoning, best quality |

## Requirements

### Hardware
- **RAM:** Minimum 16GB for 9B model, 32GB+ for 35B model
- **GPU** (optional but recommended):
  - 9B Q4: 6-8GB VRAM for full GPU offload
  - 35B Q4: 24GB+ VRAM for full GPU offload

### Software
- llama.cpp built with CUDA support (for GPU acceleration)
- Git (for cloning llama.cpp repo)

## Related

* [Installation](/tools/ornith-llama-cpp-setup/installation.md) — How to set up the server
* [GPU Offloading](/tools/ornith-llama-cpp-setup/gpu-offloading.md) — Layer allocation by VRAM