Modele AI NVIDIA

NVIDIA: Llama Nemotron Embed VL 1B V2 (free) is included in the AIToolly model catalog.

Kontekst

131K

Wejście

0,00 USD

Wyjście

0,00 USD

Llama Nemotron Rerank VL 1B V2 is a 1.7B multimodal reranking model from NVIDIA. It evaluates the relevance of document images and text against user queries, designed for vision RAG…

Kontekst

10K

Wejście

0,00 USD

Wyjście

0,00 USD

NVIDIA Nemotron 3 Embed 1B is an open text embedding model from NVIDIA, optimized for high-throughput, low-latency retrieval. It is suited for enterprise search, RAG, code retrieval, and agentic retrieval…

Kontekst

33K

Wejście

0,00 USD

Wyjście

0,00 USD

Nemotron-3-Nano-30B-A3B-BF16 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be configured through a flag in the chat template. If the user prefers the model to provide its final answer without intermediate reasoning traces, it can be configured to do so, albeit with a slight decrease in accuracy for harder prompts that require reasoning. Conversely, allowing the model to generate reasoning traces first generally results in higher-quality final solutions to queries and tasks.

Kontekst

262K

Wejście

0,05 USD

Wyjście

0,20 USD

NVIDIA Nemotron 3 Nano Omni is a multimodal large language model that unifies video, audio, image, and text understanding to support enterprise-grade Q&A, summarization, transcription, and document intelligence workflows. It extends the Nemotron Nano family with integrated video+speech comprehension, Graphical User Interface (GUI), Optical Character Recognition (OCR), and speech transcription capabilities, enabling end-to-end processing of rich enterprise content such as meeting recordings, M&E assets, training videos, and complex business documents. NVIDIA Nemotron 3 Nano Omni was developed by NVIDIA as part of the Nemotron model family.

Kontekst

256K

Wejście

0,00 USD

Wyjście

0,00 USD

> Use temperature=1.0 and top_p=0.95 across **all tasks and serving backends** — reasoning, tool calling, and general chat alike.

Kontekst

262K

Wejście

0,085 USD

Wyjście

0,40 USD

For more details on how to deploy and use the model - see the Quick Start Guide below!

Kontekst

512K

Wejście

0,60 USD

Wyjście

3,6 USD

Nemotron 3.5 ASR Streaming Multilingual 0.6B is a speech recognition model from NVIDIA. Its prompt-conditioned, cache-aware FastConformer-RNNT design targets low-latency transcription across more than 40 languages for real-time captioning, voice…

Kontekst

0

Wejście

3,33 USD

Wyjście

0,00 USD

NVIDIA: Nemotron 3.5 Content Safety (free) is included in the AIToolly model catalog.

Kontekst

128K

Wejście

0,00 USD

Wyjście

0,00 USD

NVIDIA Nemotron™ is a family of open models with open weights, training data, and recipes, delivering leading efficiency and accuracy for building specialized AI agents.

Kontekst

262K

Wejście

0,08 USD

Wyjście

0,20 USD

NVIDIA: Nemotron Nano 12B 2 VL (free) is included in the AIToolly model catalog.

Kontekst

128K

Wejście

0,00 USD

Wyjście

0,00 USD

NVIDIA-Nemotron-Nano-9B-v2 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be controlled via a system prompt. If the user prefers the model to provide its final answer without intermediate reasoning traces, it can be configured to do so, albeit with a slight decrease in accuracy for harder prompts that require reasoning. Conversely, allowing the model to generate reasoning traces first generally results in higher-quality final solutions to queries and tasks.

Kontekst

128K

Wejście

0,00 USD

Wyjście

0,00 USD

Parakeet TDT 0.6B v3 is NVIDIA's 600M-parameter multilingual speech-to-text model built on the FastConformer-TDT architecture. Trained on the Granary dataset (670,000+ hours of audio), it supports automatic language detection across…

Kontekst

0

Wejście

1500 USD

Wyjście

0,00 USD