Cosmos 3 Edge
Cosmos 3 Edge is an omnimodal world model developed by NVIDIA, designed as a foundation for Physical AI applications such as robotics and autonomous driving. It is best at generating dynamic, high-quality video, image, audio, and action commands from combinations of text, image, video, and action trajectory inputs.
Input
Output
Context
131K
Max Output
-
Parameters
3.9B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Resources & Links
Estimated GPU requirements for Cosmos 3 Edge
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
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Frequently asked questions about Cosmos 3 Edge
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Cosmos 3 Edge advertises a context window of 131,072 tokens. The figure is the creator's published maximum; a given host may serve less, and the gateway routes on what each host actually serves.
Yes. Cosmos 3 Edge is an open-weight model released under the Other license, so the weights can be downloaded and self-hosted within that license's terms.
Cosmos 3 Edge accepts Text, Image, Video and Audio and produces Text, Image, Video and Audio. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for Cosmos 3 Edge is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; Cosmos 3 Edge is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
About 4.2 GB at INT8 for the weights and a default context, from the catalog's 3.9B parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Aug 28, 2026
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