DeepSeek-Pro

About

What DeepSeek-Pro is

Model Overview Description: The NVIDIA DeepSeek-V4-Pro-NVFP4 model is the quantized version of the DeepSeek-V4-Pro model, which is a Mixture-of-Experts (MoE) language model with 1.6 trillion total parameters and 49 billion activated parameters. For more information, please check here. The NVIDIA DeepSeek V4 Pro NVFP4 model is quantized with Model Optimizer. This model is ready for commercial/non-commercial use. <br Third-Party Community Consideration This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see link to Non-NVIDIA (DeepSeek V4 Pro) Model Card. License/Terms of Use: MIT Deployment Geography: Global <br Use Case: DeepSeek V4 is well-suited for advanced reasoning, agentic AI applications, tool use scenarios, and complex problem-solving in domains such as mathematics, software engineering, and enterprise AI assistants. <br Release Date: Huggingface 05/27/2026 via https://huggingface.co/nvidia/DeepSeek-V4-Pro-NVFP4 <br Model Architecture: Architecture Type: Transformers <br Network Architecture: Mixture-of-Experts (MoE) with Hybrid Attention (Compressed Sparse Attention + Heavily Compressed Attention) <br Total Parameters: 1.6 Trillion (49 Billion activated) <br Input: Input Type(s): Text <br Input Format(s): String <br Input Parameters: 1D (One Dimensional) <br Other Properties Related to Input: Supports multi-turn conversations with system prompts, user messages, and assistant responses. Maximum context length of 1 million tokens. Uses a custom encoding pipeline (encodingdsv4) with three reasoning modes: Non-think (fast), Think High (logical analysis), and Think Max (full reasoning extent). <br Output: Output Type(s): Text <br Output Format: String <br Output Parameters: 1D (One Dimensional) <br Other Properties Related to Output: Supports structured JSON output, function/tool calling, and reasoning content when enabled. <br Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA’s hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference t

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How language models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys nvidia-deepseek-pro for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (nvidia-deepseek-pro below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"nvidia-deepseek-pro","messages":[{"role":"user","content":"Hello"}]}'

Details

Languages, data & research

Licence

Open weights

Sources

Weights & code

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