Nvidia Nemotron Parse V1.2
NVIDIA develops the Nvidia Nemotron Parse V 1.2, a chat model exceling at understanding document semantics and extracting text and table elements with spatial grounding from images. It is notable for its large context window of 9,000 tokens, allowing it to process extensive documents.
Input
Output
Context
9K
Max Output
9K
Parameters
936.3M
Technical Specifications
Input Modalities
Output Modalities
Capabilities
Loading capabilities…
Resources & Links
Estimated GPU requirements for Nvidia Nemotron Parse V1.2
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.
More models by NVIDIA
The creator's other models in the catalog, with their context, size and license where published.
Compare it, or keep browsing
Put this model beside its alternatives on the same evidence, or go back to the full catalog.
Frequently asked questions about Nvidia Nemotron Parse V1.2
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Nvidia Nemotron Parse V1.2 advertises a context window of 9,000 tokens, with a maximum output of 9,000 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. Nvidia Nemotron Parse V1.2 is an open-weight model released under the Other license, so the weights can be downloaded and self-hosted within that license's terms.
Nvidia Nemotron Parse V1.2 accepts Text and 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 Nvidia Nemotron Parse V1.2 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; Nvidia Nemotron Parse V1.2 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 1.4 GB at INT8 for the weights and a default context, from the catalog's 936.3M 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
Put intelligence in the middle.
One gateway in front of every model, with your policies applied and every decision on record. Start with $5 of credit and 5,000 routing decisions a month, no card required.