Intel / post

AA-Robotics v0.1 benchmarks frontier LLMs on robot arms

Source: x.com
Date: Published Oct 14, 2026

Why it matters

Frontier models in coding harnesses can now operate a robot arm for simple tasks, but run far too slowly and expensively for production. The gives a baseline for tracking when that changes.

Key takeaways · AI-distilled

In AA-Robotics v0.1, each model controls a 6-axis arm through a simple HTTP API, sees the scene through four cameras, and writes code to plan moves. Attempts are zero-shot and graded on the end state, with partial credit for incomplete attempts.
Across the first eight tasks, GPT-6 Astra leads at 69, ahead of GPT-6.1 Sol at 65, Gemini 4 Argon at 55, Claude Opus 5.5 at 49 and Claude Fable 5.1 at 46.
Models take about 30 minutes per tabletop task on average. Cost ranges from $1.93 per task for GPT-6.1 Sol to $16.36 for GPT-6 Astra, more than eight times as much.
Artificial Analysis estimates the best models are about 100x slower and 10x more expensive than a human, far from production use, though it expects that gap to close quickly.

Terms in this piece · Glossary

AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
benchmark — A standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.

Read the source x.com