Dell + Hugging Face

Take open AI from model to production on premises.

Discover validated models, deployable applications, and hardware-aware configurations engineered for secure AI on Dell infrastructure.

New dell-ai brings catalog discovery, configuration, and deployment to your terminal.
Model catalog

Latest optimized models

Recently added open models, ready for Dell infrastructure.

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Mistral Large 4 1T A52B

Deployable
1.1T
Other
3 Platforms

New Mistral Large 4 is a multimodal, multilingual Mixture-of-Experts model with 1.05T total and 49B active parameters and a 1M-token context window. It takes text and images as input and generates text, with particular strengths in cybersecurity, coding agents, and multimodality.

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Mistral Large 4 1T A52B NVFP4

Deployable
1.1T
Other
1 Platform

New Mistral’s NVFP4-optimized variant of Mistral Large 4, a multimodal, multilingual Mixture-of-Experts model with 1.05T total and 49B active parameters and a 1M-token context window. It takes text and images as input and generates text for cybersecurity, coding agents, and multimodal workloads.

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DeepSeek V4.1 Flash 1017

Deployable
284B
MIT
8 Platforms

New Updated Mixture-of-Experts model with improved reasoning, coding, agentic capabilities, and visual understanding, with shorter outputs and faster task execution.

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Google EmbeddingGemma 2

Deployable
740M
Apache 2.0
2 Platforms

New Multimodal embedding model with 740M parameters that maps text, images, video, and audio into a shared 768-dimensional vector space for semantic search, retrieval, classification, and clustering.

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Beam 1.0 501B A23B BF16

Deployable
501B
Apache 2.0
3 Platforms

New Reflection’s BF16 MoE model with 501B total and 23B active parameters, a 1M-token context window, and reasoning, coding, and tool-use capabilities.

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Beam 1.0 501B A23B NVFP4

Deployable
501B
Apache 2.0
6 Platforms

New Reflection’s NVFP4 MoE model with 501B total and 23B active parameters, a 1M-token context window, and reasoning, coding, and tool-use capabilities.

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Newsroom

Latest updates

New models, platform support, and practical deployment guidance.

Introducing Mistral Large 4 on Dell Enterprise Hub

Mistral Large 4 is a multimodal, multilingual Mixture of Experts model from Mistral. It takes text and images as input and generates text, with 1.05T total parameters, 49B active parameters per token (52B including embeddings and output layers), and a context window of 1M tokens. Today, we are releasing both FP8 and NVFP4 variants to the catalog. Deploy Mistral Large 4 FP8 → · Deploy Mistral Large 4 NVFP4 →

DeepSeek V4.1 Flash 1017 and EmbeddingGemma 2 land on Dell Enterprise Hub

DeepSeek V4.1 Flash 1017 improves reasoning, coding, agentic tasks, and visual understanding while reducing task execution time and output length. Deploy it with vLLM v0.32.0 on NVIDIA H100, H200, and B300 or AMD MI300X and MI355X systems. Google EmbeddingGemma 2 brings text, image, video, and audio embeddings into a shared vector space for semantic search and retrieval. Deploy it with hf serve v0.2.0 on 1× NVIDIA L40S or Dell Pro Max with GB10. Deploy DeepSeek V4.1 Flash 1017 → · Deploy EmbeddingGemma 2 →

Introducing Reflection Beam 1.0 on Dell Enterprise Hub

Beam 1.0 by Reflection is now available in BF16 and NVFP4 on Dell Enterprise Hub. This MoE model combines 501B total and 23B active parameters with a 1M token context window for reasoning, coding, and agentic tool use. Reflection reports comparable reasoning quality to leading open models using approximately 3× fewer reasoning tokens. Deploy NVFP4 on 4× NVIDIA H100 or 4× and 8× H200 and B300, with DFlash speculative decoding on B300. Deploy BF16 on 8× H200 or B300. Deploy Beam 1.0 BF16 → · Deploy Beam 1.0 NVFP4 →

Now available: Muse Spark Open NVFP4 and NVIDIA Nemotron 3.5 Super VL

Muse Spark Open improves code generation, complex debugging, codebase understanding, and end to end developer workflows while retaining strong general agent capabilities. Deploy the NVFP4 variant with SGLang v0.5.21. NVIDIA Nemotron 3.5 Super VL combines reasoning, coding, and tool use with document and video understanding. Its BF16 release offers 120B total and 12B active parameters, up to 1M tokens of context, and native MTP speculative decoding. Deploy with vLLM v0.31.0. Deploy Muse Spark Open NVFP4 → · Deploy Nemotron 3.5 Super VL →

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Application catalog

Deploy complete AI applications

Go beyond endpoints with production-ready AI experiences.

Super Analyzer

Super Analyzer is an application that identifies and evaluates common anti-patterns in C++, Java, Python, and Rust code. It uses a multi-agent architecture with three coordinated agent types—Primary, Fixer, and Chat—to deliver accurate analysis and iterative improvements. The Web UI supports natural multi-turn interactions and uses a PostgreSQL database to persist in user accounts and conversation history across sessions. Super Analyzer also provides a REST/API layer and a Python interface, all secured through user/password authentication backed by PostgreSQL. Access is protected with JWTs signed using RSA-256, ensuring a consistent and secure experience across all entry points.

nvidianemotronmulti-agent

OpenWebUI

OpenWebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline. It provides a modern interface for interacting with various LLM runners including Ollama and OpenAI-compatible APIs. With built-in RAG (Retrieval Augmented Generation) capabilities, OpenWebUI offers a comprehensive solution for AI deployment and interaction in Kubernetes environments.

chatllmmulti-modal

AnythingLLM

AnythingLLM is an open-source, all-in-one AI chat application with built-in RAG (Retrieval Augmented Generation) capabilities. It provides a user-friendly interface for document management, LLM integration, and AI agent creation - all without complex setup. The application supports both local and cloud-based deployments, making it ideal for teams and organizations seeking a private, customizable AI solution.

chatragagents

Agentic Smart Router

In an Agentic AI application, not all prompts are the same, different prompts need to have different requirements in terms of complexity of the prompt - some need reasoning, some need access to RAG system and some need tool calling capabilities. In this custom-built Agentic Smart Router, we demonstrate that capability by leveraging NVIDIA Agent Intelligence Toolkit, NVIDIA NIMs, NVIDIA LLM Router blueprint and stitching them together to build an Agentic Smart Router application.

nvidianimsagents
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