DeepSeek-Flash-DSpark

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What DeepSeek-Flash-DSpark is

Model Overview Description: The NVIDIA DeepSeek-V4-Flash-nvfp4-DSpark model is a quantized version of DeepSeek AI's DeepSeek-V4-Flash model, an autoregressive Mixture-of-Experts language model that uses an optimized Transformer architecture with hybrid attention (Compressed Sparse Attention and Heavily Compressed Attention) and Manifold-Constrained Hyper-Connections, packaged in a single checkpoint together with DeepSeek's official DSpark speculative decoding module. For more information, refer to the DeepSeek-V4-Flash model card and the DeepSeek-V4-Flash-DSpark model card. The NVIDIA DeepSeek-V4-Flash-nvfp4-DSpark model is quantized with Model Optimizer. Note: DeepSeek-V4-Flash-nvfp4-DSpark is not a new model. It is the NVFP4 backbone of nvidia/DeepSeek-V4-Flash-NVFP4 with DeepSeek's official DSpark speculative decoding module attached, so a single checkpoint serves as both target and draft model. For more details on DSpark, refer to: https://github.com/deepseek-ai/DeepSpec 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-Flash-DSpark) Model Card. References - Nvidia Model Optimizer: https://github.com/NVIDIA/Model-Optimizer - DeepSeek-V4-Flash base model card - DeepSeek-V4-Flash-DSpark model card - nvidia/DeepSeek-V4-Flash-NVFP4 model card - DeepSeek-V4 technical report - DeepSeek DSpec reference implementation: https://github.com/deepseek-ai/DeepSpec 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: Hugging Face 07/22/2026 via https://huggingface.co/nvidia/DeepSeek-V4-Flash-nvfp4-DSpark <br Model Architecture: Architecture Type: Transformers <br Network Architecture: Mixture-of-Experts (MoE) with Hybrid Attention (Compressed Sparse Attention + Heavily Compressed Attention) <br Number of

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

Specifications

What it is

How it works

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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-flash-dspark for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (nvidia-deepseek-flash-dspark 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-flash-dspark","messages":[{"role":"user","content":"Hello"}]}'

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