DeepSeek-V4-Flash

DeepSeek-V4-Flash

DeepSeek's preview mixture-of-experts language model with 284B parameters, 13B used per token and a one million token context. The smaller sibling of DeepSeek-V4-Pro. For labs and heavy self-hosting.

Made by deepseek-ai on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.

About

What it is: DeepSeek-V4-Flash is a preview language model from DeepSeek. It is a mixture-of-experts model with 284 billion parameters in total, and 13 billion are active for each token. It supports a context of one million tokens.

It belongs to the DeepSeek-V4 series, which also has DeepSeek-V4-Pro at 1.6 trillion parameters. Both were pre-trained on more than 32 trillion tokens, then post-trained in two stages.

Who it suits: Research labs and teams with large hardware who want an open model for long documents, coding and reasoning.

Industry | Who uses it | How they use it | Example
Research | Language model labs | Study a long-context open model | Compare it with the Pro model
Software | Teams with large servers | Host a strong open model themselves | Run coding and reasoning tasks
Enterprise | Data and AI teams | Work over long documents | Read a large collection in one pass

Skip it if you have an ordinary computer, since the files alone are about 291 GB.

Where to use it:

• A serving setup that can load huge Safetensors files, as the model card describes
• Hugging Face Transformers, which the library tag lists
• Windows, macOS or Linux with Python, to download the files

Use case | Who | What they get back
Long-context work | Researchers | Answers over inputs of up to one million tokens
Coding and reasoning | Developers | Text from a model that can think longer when allowed
Self-hosting | Platform teams | An open model they run on their own servers

How to set it up:

• Python and pip to run the download commands
• Storage for about 291 GB of files
• Serving hardware far beyond a normal PC, following the model card

1. Install the Hugging Face tools.
2. Download the model files.
3. Load them in your serving setup using the model card.

pip install -U huggingface_hub
hf download deepseek-ai/DeepSeek-V4-Flash

How to use it: Load the model in a serving setup that fits its size, then send prompts as text. The card describes a Max mode with a larger thinking budget, which gets reasoning close to the Pro model.

Property | DeepSeek-V4-Flash
Total parameters | 284B
Active per token | 13B
Context length | 1M tokens
Precision | A mix of FP4 and FP8
Pre-training data | More than 32T tokens

Example: You load the model on a large server and give it a long codebase together with a question. It reads the whole input in one go and replies in text.

For newcomers and experts: If you are new to large models, this one is not the place to start, because it needs huge hardware. Try a smaller model first.

If you know the field, the series uses a hybrid of Compressed Sparse Attention and Heavily Compressed Attention, plus manifold-constrained hyper-connections and the Muon optimizer. The post-training trains domain experts first, then merges them with on-policy distillation.

Download the model files
Load them on large hardware
Send a long prompt
Receive text, with optional extra thinking

Good to know:

• This is a preview version of the series
• The card says the Flash model slightly trails Pro on pure knowledge and the hardest agent tasks
• The efficiency figures on the card of 27 percent of the compute and 10 percent of the cache are for the Pro model against V3.2
• Hugging Face lists 137 quantized and 28 fine-tuned versions made by other people
• License: MIT
• Cost to run: none named, though the hardware is expensive
• Data it reaches: the files you download and the prompts you give it
• Not for: ordinary computers

On Hugging Face, 13 November 2026

• Task: text generation
• Library: transformers
• Parameters: 291B
• Weights: about 291 GB in I8
• Formats: Safetensors
• Downloads in the last 30 days: 1,192,571
• Likes: 2,393
• License: mit
• Quantized versions: 138
• Fine-tunes: 28
• Tags: transformers, safetensors, deepseek_v4, text-generation, 8-bit, fp8

Links

• Model: https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash
• Files: https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash/tree/main

Get the model

Download its files with Hugging Face's command line:

pip install -U huggingface_hub
hf download deepseek-ai/DeepSeek-V4-Flash

Then follow the usage in its model card. Nothing in this kit runs by itself.