Deberta V2 Xlarge
Deberta V2 Xlarge is a chat model developed by Microsoft, exceling at text generation tasks with its disentangled attention and enhanced mask decoder architecture. It achieves top-notch performance on several NLU tasks, including SST-2 with 97.5% accuracy and RTE with 93.9% accuracy, showcasing its strength in natural language understanding.
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1K
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1K
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Frequently asked questions about Deberta V2 Xlarge
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Deberta V2 Xlarge advertises a context window of 512 tokens, with a maximum output of 512 tokens in a single response. 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. Deberta V2 Xlarge is an open-weight model released under the MIT license, so the weights can be downloaded and self-hosted within that license's terms.
Deberta V2 Xlarge accepts Text and produces Text. 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 Deberta V2 Xlarge 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; Deberta V2 Xlarge 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.
Microsoft has not published a parameter count for Deberta V2 Xlarge, so the catalog cannot estimate its memory footprint. The capacity planner can size it from a parameter count you supply.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Aug 28, 2026
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