NVIDIA Nemotron Nano 12B Alternatives

This is a 12 billion parameter vision-language variant of NVIDIA's Nemotron-Nano-2 model, provided in NVFP4 quantized format for efficient inference. It supports multimodal inputs including images and text, and includes capabilities for tool calling and reasoning. The model is distributed on Hugging Face for use by developers building vision-language applications on NVIDIA infrastructure.

NVIDIA's Nemotron Nano 12B v2 is a vision-language (VL) model provided in BF16 precision. It combines language understanding with visual processing capabilities in a relatively compact 12 billion parameter model. The model is hosted on Hugging Face and is suitable for multimodal tasks requiring both image and text understanding.

NVIDIA Nemotron-Nano-9B-v2 is an open 9 billion parameter language model designed for high performance on tool-calling, function calling, and reasoning tasks. It features a specialized system prompt format and is distributed on Hugging Face for integration into agentic workflows and local inference.

NVIDIA-Nemotron-3-Nano-30B-A3B-FP8 is an FP8-quantized version of NVIDIA's Nemotron-3 language model. It includes optimized chat templates and is designed for efficient inference. Hosted on Hugging Face, it targets developers and researchers needing high-performance language models that can run with lower memory and compute requirements on compatible NVIDIA systems.

NVIDIA-Nemotron-Nano-9B-v2-FP8 is a 9 billion parameter language model published on Hugging Face. It provides optimized FP8 weights for efficient inference while supporting advanced features such as tool calling and custom chat templates. The model is intended for developers who want to run or fine-tune capable open-weight LLMs either locally or through inference providers.

NVIDIA Nemotron-3 Nano 30B (A3B Base BF16) is an open-source large language model designed for text generation. It offers strong performance with a mixture-of-experts or optimized architecture suitable for enterprise and research applications. The model is hosted on Hugging Face and can be used with the Transformers library for inference, fine-tuning, or integration into custom AI pipelines.

This is an AWQ-quantized version of NVIDIA's Nemotron-3 Nano 30B (A3B) model. It is a large language model optimized for efficient inference while preserving performance. The model is suitable for various text generation and instruction-following tasks and is compatible with the Hugging Face ecosystem.

NVIDIA-Nemotron-3-Nano-4B-FP8 is a 4 billion parameter language model from NVIDIA, provided in FP8 precision for optimized performance on NVIDIA hardware. It supports text generation and chat applications using a custom chat template. The model is designed for developers building efficient AI applications that leverage NVIDIA GPUs for local or on-premise inference.

NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4 is an open large language model released by NVIDIA for advanced text generation tasks. It is designed for AI research, experimentation, and integration into downstream applications. The model is available under an open license for developers and researchers.

NVIDIA Nemotron-3 Super 120B A12B GGUF is an open-source large language model distributed in GGUF format for local inference. It enables developers and researchers to run advanced text generation tasks on their own hardware, supporting experimentation and customization without cloud dependencies.

NVIDIA Nemotron-3 Super is a 120B parameter language model with an A12B active parameter count. The FP8 version provides efficient inference while maintaining model quality. It uses a mixture-of-experts architecture and is designed for high-performance text generation tasks. The model is available on Hugging Face for developers and researchers.

Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4 is an open-source large language model by NVIDIA, designed for advanced reasoning and text generation. It is suitable for researchers and developers building AI-powered applications.

This is a community-quantized 4-bit AWQ version of NVIDIA's Nemotron-3 Super 120B parameter language model. It enables efficient local or self-hosted inference of a powerful open-weights LLM using significantly less GPU memory than the original. The repository provides model weights, tokenizer configuration, and chat templates for integration with popular inference frameworks like Transformers or vLLM.

Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8 is an NVIDIA-published multimodal reasoning model optimized with FP8 precision for efficient inference. It combines language, vision, and reasoning capabilities in a compact form factor suitable for on-premise or cloud deployment. The model targets developers and researchers building advanced AI systems.

This is a quantized (NVFP4) version of NVIDIA's Nemotron-3 Ultra 550B model with 55B active parameters. It is designed for high-quality text generation and is released under an open model license. The model is hosted on Hugging Face and optimized for NVIDIA inference hardware and software.

NVIDIA Nemotron-3 Ultra is a massive 550 billion parameter (with 55B active) mixture-of-experts model released in BF16 format. It is designed for high-quality text generation and complex reasoning. The model is hosted on Hugging Face and targets developers and enterprises needing state-of-the-art open language model capabilities.

Nemotron-H-8B-Base-8K is an 8 billion parameter base language model from NVIDIA. It supports an 8K token context window and is designed as a foundation for further specialization. The model is hosted on Hugging Face and intended for researchers and developers building custom LLMs.

NVIDIA Nemotron Parse v1.2 is an image-text-to-text model designed for document understanding and parsing tasks. It accepts both visual and textual inputs and produces structured outputs. The model is available on Hugging Face with Transformers support and is part of NVIDIA's Nemotron family of models.

NVIDIA-Nemotron-Parse-v1.1 is an image-text-to-text model developed by NVIDIA for multimodal parsing tasks. It processes both visual and textual inputs to generate structured outputs. The model is available on Hugging Face, supports the Transformers library, and is suitable for developers building vision-language applications.

Nemotron-Cascade-2-30B-A3B is an open-source large language model released by NVIDIA, designed for text generation and AI research. It provides open weights, supports local inference, and is suitable for researchers and developers working on advanced language AI projects.

Nemotron-Mini-4B-Instruct is a small yet powerful instruction-tuned model developed by NVIDIA. It is designed for low-latency inference on edge devices while maintaining strong reasoning and tool-use capabilities. The model uses a custom chat template and supports function calling.

NVIDIA's Nemotron-3-Embed-8B-BF16 is an 8 billion parameter embedding model optimized for sentence similarity and semantic feature extraction. It is compatible with the sentence-transformers library and can be used for RAG pipelines, semantic search, and clustering. The model is available in BF16 precision on Hugging Face.

Nemotron-3-Embed-1B-BF16 is NVIDIA's 1 billion parameter embedding model optimized in BF16 precision. It is designed for high-performance sentence similarity and semantic retrieval. Available on Hugging Face for integration into RAG, search, and recommendation systems.

Nemotron-Labs-Diffusion-14B is an open-source large language model released by NVIDIA for advanced text generation tasks. It is designed for AI researchers and developers to experiment with, fine-tune, and deploy in various natural language processing applications. The model is available via Hugging Face with open weights and supports both local and cloud inference.