Two 3GB models plus an arbiter: 64% of clinical decisions run locally at 91.9% accuracy
MaziyarPanahi · x · 2026-10-08
Developer MaziyarPanahi demoed a single-machine model cascade: two 3GB local models answered 669 clinical decisions, with Mistral Large 4 stepping in only on disagreements or urgency/red-flag questions. Result: 64% answered fully locally, 91.9% accuracy, zero severe misses — level with Mistral alone. Scoring followed the same strict rubric as the reference board, computed from each model's logged answers. The escalate-only-when-needed pattern is a practical blueprint for cost- and privacy-sensitive deployments.
Related event: Two 3GB Local Models Handle 64% of Clinical Decisions with 91.9% Accuracy(2 posts)→
More from coding & agent
- A Developer's Map of the Data Tooling Landscape: Ingestion, Storage, Modeling, Governance — bibryam · 2026-10-08
- Operator-1 launches as autonomous document extraction agent for long tables and sprawling PDFs — ycombinator · 2026-10-08
- good-css: 47 modern CSS techniques that make coding agents actually use :has() and subgrid — mattpocockuk · 2026-10-08
- Microsoft launches Azure canvases: an interactive shared workspace for Copilot agents — adnan_hashmi · 2026-10-08
- ChatGPT Work mode vs Codex: same quota, far more tasks done per 5-hour window — sasik520 · 2026-10-08
- Redditor complains Sonnet + Haiku agent swarm wrecks codebase whenever Opus budget runs out — MucilaginusCumberbun · 2026-10-08