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RLinf adds Cosmos3 support for fine-tuning and robot evaluation

LMSYS reports 3.33× end-to-end evaluation throughput with SGLang, which batches inference for 128 parallel environments on eight GPUs.

Ying ShengYS
LMSYS OrgLO
2 Sources, 20d ago, first seen 20d ago

TLDR

LMSYS announced that RLinf, an open-source framework for embodied intelligence and AI agents, now supports Cosmos3 from fine-tuning to robot evaluation. It reports 3.33× end-to-end evaluation throughput with SGLang, describing a setup covering 500 episodes of the full LIBERO-10 evaluation with 128 parallel environments and eight GPUs. LMSYS says RLinf overlaps CPU simulation with GPU inference to reduce waiting between stages.

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2 Sources, first seen 20d ago

68 likes14 comments25 saves13 reposts

Combined views

3.5K

2 Sources, first seen 20d ago

68 likes14 comments25 saves13 reposts

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2 Sources

LMSYS Org@lmsysorg🚀 New blog: Cosmos3 in RLinf: 3.33× End-to-End Evaluation Throughput with SGLang RLinf is an open-source framework designed for embodied intelligence & AI agents. It now supports Cosmos3 from fine-tuning to robot evaluation. With SGLang inference support, we deliver 3.33× end-to-end evaluation throughput Highlights: - SGLang batches inference for 128 parallel environments on 8 GPUs. Covering 500 episodes of the full LIBERO-10 evaluation. - RLinf overlaps CPU simulation with GPU inference to reduce waiting between stages. Thanks to the RLinf team for the integration! Read the full blog below 👇20d
Ying Sheng@ying11231RT @lmsysorg: 🚀 New blog: Cosmos3 in RLinf: 3.33× End-to-End Evaluation Throughput with SGLang RLinf is an open-source framework designed…20d
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    2 Sources

    LMSYS Org@lmsysorg🚀 New blog: Cosmos3 in RLinf: 3.33× End-to-End Evaluation Throughput with SGLang RLinf is an open-source framework designed for embodied intelligence & AI agents. It now supports Cosmos3 from fine-tuning to robot evaluation. With SGLang inference support, we deliver 3.33× end-to-end evaluation throughput Highlights: - SGLang batches inference for 128 parallel environments on 8 GPUs. Covering 500 episodes of the full LIBERO-10 evaluation. - RLinf overlaps CPU simulation with GPU inference to reduce waiting between stages. Thanks to the RLinf team for the integration! Read the full blog below 👇20d
    Ying Sheng@ying11231RT @lmsysorg: 🚀 New blog: Cosmos3 in RLinf: 3.33× End-to-End Evaluation Throughput with SGLang RLinf is an open-source framework designed…20d
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