Ornith-35B Tops Local Coding Bench: Hits 70%+ on Strix Halo APU
przbadu · reddit · 2026-08-04
A developer tested the newly released open-source model Ornith-1.0-35B (Q8 quantization) on a mini PC powered by an AMD Strix Halo APU (128GB RAM).
On the pi-local-coding-bench, the model scored impressively high—70% and 72% as judged by Opus 5 and Gemini 1.5 Pro, respectively. More notably, it completed the 50-task benchmark in under 9 minutes, compared to over 16 minutes for larger models, demonstrating exceptional efficiency for local execution.
More from coding & agent
- Snorkel AI Builds Simulated Enterprise Environments to Train AI Agents on Complex Workflows — ajratner · 2026-08-05
- Minnow: Open-Source AI Workspace Integrating Chat, Deep Research, and Multi-Agent Orchestration — MinnowAI · 2026-08-05
- Goodfire Launches Silico Platform for Frontier-Scale Model Interpretability and Training — Jeande_d · 2026-08-05
- Grok Integrated into GitHub Copilot: Testing its App Building Capabilities — DanWahlin · 2026-08-05
- AI Agent Installs Dual-Boot System in Seconds for Just $0.01 — yacineMTB · 2026-08-05
- Podcast Explores Personal AI Agent Development: From Solving Self Needs to Shipping — msg · 2026-08-05