Kosmos 2 Patch 14 224
Kosmos 2 Patch 14 224 is a vision model developed by Microsoft, capable of performing various tasks such as phrase grounding, referring expression comprehension, and grounded visual question answering. It is genuinely best at tasks that involve multimodal grounding and perception-language understanding.
Input
Output
Context
2K
Max Output
0K
Parameters
1.7B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Resources & Links
Estimated GPU requirements for Kosmos 2 Patch 14 224
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 Kosmos 2 Patch 14 224
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Kosmos 2 Patch 14 224 advertises a context window of 2,048 tokens, with a maximum output of 128 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. Kosmos 2 Patch 14 224 is an open-weight model released under the MIT license, so the weights can be downloaded and self-hosted within that license's terms.
Kosmos 2 Patch 14 224 accepts Image 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 Kosmos 2 Patch 14 224 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; Kosmos 2 Patch 14 224 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 2.3 GB at INT8 for the weights and a default context, from the catalog's 1.7B 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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