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DeepSeek-V4-Pro: NVIDIA Launches World's Largest Open-Source LLM at 1.6T Parameters

NVIDIA AI announces DeepSeek-V4-Pro, a 1.6T parameter open-source model now available on build.nvidia.com. The model is optimized for NVIDIA Blackwell GPUs and accessible via the NVIDIA NIM API. While the announcement lacks architecture details or benchmarks, the release of a 1.6T parameter open-source model with NIM API access represents a notable developer resource.

NVIDIA AIFriday, April 24, 2026Original source
#OpenSource#LLM#Inference#API#NVIDIA

DeepSeek-V4-Pro: NVIDIA Launches World's Largest Open-Source LLM at 1.6T Parameters

Summary

DeepSeek-V4-Pro is an NVIDIA-hosted 1.6T parameter open-source language model accessible via the NVIDIA NIM API on Blackwell GPUs. While the scale is verified, architecture details and benchmarks remain undisclosed—treat this as an API evaluation opportunity until technical documentation appears.

Integration Strategy

When to Use This?

  • API-based inference: Need frontier-scale model capabilities without managing infrastructure
  • Benchmark comparison: Evaluating against current open-source leaders for your use case
  • Prototyping: Rapid assessment of 1.6T-scale capabilities before committing to specific model
  • NVIDIA ecosystem projects: Applications already leveraging or planning NVIDIA AI infrastructure

How to Integrate?

  1. Endpoint access: https://build.nvidia.com/deepseek-ai/deepseek-v4-pro
  2. Authentication: Requires NVIDIA developer account
  3. API format: Likely standard chat completions format
  4. SDK: NVIDIA NIM Python SDK available
  5. Local deployment: Not available (verify if weights released separately)

Migration path: If currently using DeepSeek-V3 via self-hosted or API, switching to V4-Pro requires adopting the NIM API interface. No fine-tuning capability via this endpoint.

Compatibility

  • API design: REST-based, framework-agnostic
  • Python SDK: Official NVIDIA NIM SDK supports this endpoint
  • Blackwell optimization: Native hardware optimization for inference
  • Self-hosted option: Check if DeepSeek releases weights separately (V3 weights were publicly released)

Source: @NVIDIAAIDev Reference: NVIDIA Build - DeepSeek-V4-Pro (build.nvidia.com) Published: 2026-04-24 DevRadar Analysis Date: 2026-04-24