docs: rebuild KB in OKF v0.1 with live-verified facts

Copy of the legacy ~/.pi/agent/docs tree rebuilt as the command-center knowledge base: concept files promoted to path identity, index listings stripped of frontmatter, all wikilinks/relative links resolved, every checkable claim verified against the live fleet (Dankserver = Ryzen 7 7700X + RTX 3090; Strix Halo is Dankclaw), unverifiable claims tagged. kb-lint exits 0.
2026-08-28 07:57:13 -07:00
parent 552d1ef8bf
commit 02883d3ed2
116 changed files with 13008 additions and 0 deletions
@@ -0,0 +1,65 @@
+---
+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