Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
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Page Freshness
Canonical route: /signal-canvas/cosmos-3-omnimodal-world-models-for-physical-ai
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID cosmos-3-omnimodal-world-models-for-physical-ai | Route /signal-canvas/cosmos-3-omnimodal-world-models-for-physical-ai
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/cosmos-3-omnimodal-world-models-for-physical-aiMCP example
{
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"mode": "paper",
"paper_ref": "cosmos-3-omnimodal-world-models-for-physical-ai",
"query_text": "Summarize Cosmos 3: Omnimodal World Models for Physical AI"
}
}source_context
{
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"mode": "paper",
"query": "Cosmos 3: Omnimodal World Models for Physical AI",
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}Claims: 12
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: Cosmos 3: Omnimodal World Models for Physical AI
PDF: https://arxiv.org/pdf/2606.02800v1
Repository: https://github.com/nvidia/cosmos
Source count: 4
Coverage: 83%
Last proof check: 2026-06-03T20:33:01.150Z
Signal Canvas receipt window
/buildability/cosmos-3-omnimodal-world-models-for-physical-ai
Subject: Cosmos 3: Omnimodal World Models for Physical AI
Verdict
Build Now
Verdict is Build Now because viability and implementation proof cleared the Wave 1 scaffold thresholds.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Preparing verified analysis
Dimensions overall score 9.0
T2V-720p T2I-720p T2V-720p multi-GPU |297.3 PyTorch-OSS| | |---|---| |286.33 vLLM-Omni| | |114.8 107.8|8| | | | |4.21 PyTorch-OSS| |---| |3.44 2.87 vLLM-Omni| | | |1
Implication not extracted yet.
partial
a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-transformers architecture.
Directly stated in the abstract with explicit enumeration of modalities.
partial
Our evaluation demonstrates that Cosmos 3 establishes a new state-of-the-art across a diverse suite of understanding and generation tasks
Explicitly claimed in the abstract, though specific tasks and metrics are not detailed in the provided excerpt.
partial
Our post-trained Cosmos 3 models were ranked as the best open-source Text-to-Image and Image-to-Video models by Artificial Analysis
Directly stated in the abstract with a specific ranking source.
partial
the best policy model by RoboArena at the time the technical report was written.
Directly stated in the abstract with a specific ranking source.
partial
within a unified mixture-of-transformers architecture.
Directly stated in the abstract.
partial
effectively subsuming vision-language models, video generators, world simulators, and world-action models into a single framework.
Directly stated in the abstract, though the exact scope of 'subsumes' may require further clarification.
partial
we make our code, model checkpoints, curated synthetic datasets, and evaluation benchmark available under the Linux Foundation's OpenMDW-1.1 https://openmdw.ai/license/1-1/ License
Directly stated in the abstract with a specific license and repository links.
partial
We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-transformers architecture.
Directly stated in the abstract with clear enumeration of modalities and architecture.
partial
Our evaluation demonstrates that Cosmos 3 establishes a new state-of-the-art across a diverse suite of understanding and generation tasks
Explicitly claimed in the abstract, though specific tasks and metrics are not detailed in the provided excerpt.
partial
Our post-trained Cosmos 3 models were ranked as the best open-source Text-to-Image and Image-to-Video models by Artificial Analysis
Directly stated in the abstract with specific ranking source.
partial
and the best policy model by RoboArena at the time the technical report was written.
Directly stated in the abstract with specific ranking source and time qualifier.
partial
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
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Receipt path
/buildability/cosmos-3-omnimodal-world-models-for-physical-ai
Paper ref
cosmos-3-omnimodal-world-models-for-physical-ai
arXiv id
2606.02800
Generated at
2026-06-03T20:33:01.150Z
Evidence freshness
fresh
Last verification
2026-06-03T20:33:01.150Z
Sources
4
References
0
Coverage
83%
Lineage hash
3970655cf2980145b5155ced621ac32a8e579963a9f25741aeb5b76fa1fca34e
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Pending verification refs / 4 sources / Verification pending
references