HELM Robo-Reward-Bench - Austin Sirius Dataset Converted Externally To Rlds: leaderboard

The "Austin Sirius Dataset Converted Externally To Rlds" subtask of HELM Robo-Reward-Bench. Stanford HELM's Robo-Reward-Bench: vision-language models act as reward models over robot manipulation episodes, predicting task progress or success from video.

Metric: Absolute Error. Source: crfm.stanford.edu. Saturation forecast: Around September 2027. 25 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Flash (Preview)0.28#84
2GPT-50.31#104
3Gemini 2.5 Pro0.33#153
4Gemini 3 Pro (Preview)0.38#66
5GPT-5 Mini (2025-08-07)0.38#174
6GPT-5.5 (xHigh)0.38#29 (GPT-5.5)
7GPT-5.5 (2026-04-23)0.39#24
8GPT-5.1 (2025-11-13)0.57#105
9Gemini 2.5 Flash Lite0.61#421
10Gemini 2.5 Flash0.66#242
11GPT-5.20.76#113
12Llama 4 Maverick Instruct1.02#460
13Llama 4 Scout Instruct1.24#542
14GPT-5 Nano1.34#428

No result here: #4 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=helm-robo-reward-bench-austin-sirius-dataset-converted-externally-to-rlds · How It Works · Data refreshed daily, snapshot 2026-10-23.