NVIDIA: Nemotron 3.5 Super VL

{"about":"### Reasoning, code and long-text work\n\nNemotron 3.5 Super VL is an NVIDIA model for tasks requiring several connected reasoning steps, understanding program code or processing substantial material. This Ailoot API listing provides text conversations: you supply instructions, source data and message history, and the model returns a text response.\n\nUse it to analyze technical documentation, compare requirements, prepare code explanations and examine text reports. State the goal, include the necessary material and define the result’s form—for example, a list of conclusions with supporting reasoning, a program-change plan or a comparison of several solutions.\n\n### Architecture and specialization\n\nThe underlying Super VL is an NVIDIA vision-language model with a C-RADIO vision encoder, also designed to understand documents and video. This Ailoot API listing provides its text capabilities; source material is supplied as text content.\n\nThe model’s backbone combines Mamba-2, Transformer and Mixture of Experts architectures. Approximately 12 billion of its roughly 120 billion parameters are active at a processing step. This describes the model’s architecture and should be considered separately from the actual speed of a particular request.\n\nTraining used software repositories, task-and-code-change pairs, build logs, multistep problem-solving trajectories and long-context material. Further training combined code, reasoning, instructions and conversation. This specialization is useful when defining a compound task in which source information must first be connected and then organized into a result.\n\n### How to prepare a task\n\nFor document analysis, first state the question and information-selection criteria, then include the text with section headings. To compare sources, give them short labels and ask for conclusions to be tied to those labels. For a coding task, add the relevant program fragment, observed behavior and expected result so the response can be checked against a specific case.\n\nA large context window helps place related material in one request. Context size does not replace a clear task definition: separate instructions from source data and specify the decision or document you want to obtain.\n\n### Context and connection methods\n\nFor this variant, Ailoot API specifies a context window of 262,144 tokens. Conversation history, instructions, source material and the response share this space; leave room for the result when preparing a long request.\n\nThe model is available through Chat Completions, Responses, Messages and a text interface in Gemini format. This variant’s available workflow is text input and text output; documents are supplied as text content.","alias_of":null,"aliases":[],"author":"NVIDIA","canonical_model":"nvidia/nemotron-3.5-super-vl","ctx":null,"formats":["chat","gemini","messages","responses"],"id":"nvidia/nemotron-3.5-super-vl","input":["text"],"kind":"text","max_out":null,"methods":[{"cache_read":0.04,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"anthropic","fast_multiplier":1,"flex_multiplier":1,"fmt":"messages","http":"POST","img_in":null,"img_out":null,"in":0.3,"input":["text"],"label":"Anthropic Messages","max_out":null,"max_tool_calls":null,"out":1.0,"output":["text"],"path":"/v1/messages","request_model_id":"nvidia/nemotron-3.5-super-vl","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.04,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"openai","fast_multiplier":1,"flex_multiplier":1,"fmt":"responses","http":"POST","img_in":null,"img_out":null,"in":0.3,"input":["text"],"label":"OpenAI Responses","max_out":null,"max_tool_calls":null,"out":1.0,"output":["text"],"path":"/v1/responses","request_model_id":"nvidia/nemotron-3.5-super-vl","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.04,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"openai","fast_multiplier":1,"flex_multiplier":1,"fmt":"chat","http":"POST","img_in":null,"img_out":null,"in":0.3,"input":["text"],"label":"OpenAI Chat","max_out":null,"max_tool_calls":null,"out":1.0,"output":["text"],"path":"/v1/chat/completions","request_model_id":"nvidia/nemotron-3.5-super-vl","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.04,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"gemini","fast_multiplier":1,"flex_multiplier":1,"fmt":"gemini","http":"POST","img_in":null,"img_out":null,"in":0.3,"input":["text"],"label":"Gemini generateContent","max_out":null,"max_tool_calls":null,"out":1.0,"output":["text"],"path":"/v1beta/models/nvidia/nemotron-3.5-super-vl:generateContent","request_model_id":"nvidia/nemotron-3.5-super-vl","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]}],"model_aliases":[{"canonical_model_id":"nvidia/nemotron-3.5-super-vl","request_model_id":"nvidia/nemotron-3.5-super-vl","route_label":"Ultra"}],"name":"NVIDIA: Nemotron 3.5 Super VL","price":{"in":0.3,"in_label":null,"out":1.0,"out_label":null,"sort_in":0.3,"sort_out":1.0,"varies":false},"public_id":"nvidia/nemotron-3.5-super-vl","short":"Text conversations with an NVIDIA model for reasoning, code work and analysis of substantial material."}