DeepSeek-V4-Flash

Updated

Thinking

Reasoning

Code

Multilingual

Run

Run DeepSeek-V4-Flash, a fast MoE model, locally in Atomic Chat. Private, offline reasoning and coding — no cloud, no limits. Free.

huggingface-cli download deepseek-ai/DeepSeek-V4-Flash

from transformers import AutoModel
model = AutoModel.from_pretrained("deepseek-ai/DeepSeek-V4-Flash")

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Name	Size / Usage	Context	Input
DeepSeek-V4-Pro		1M	Text
DeepSeek-R1-0528	Reasoning, math, coding	128K	Text
DeepSeek-V3-0324	General chat, coding, agents	128K	Text
DeepSeek-Coder-V2-Lite-Instruct	Code generation, completion	128K	Text
DeepSeek-V3.2		128K	Text
DeepSeek-R1		128K	Text

At a glance

License: Mit
Context length: 1M tokens
Languages: Multilingual
Minimum hardware: ~89 GB VRAM
Strengths: reasoning, coding and on-device inference

Overview

DeepSeek-V4-Flash is an open-weight large language model from deepseek-ai, the lab behind the DeepSeek-V3 and R1 series.

License: Mit
Context length: 1M tokens
Languages: Multilingual
Minimum hardware: ~89 GB VRAM
Strengths: reasoning, coding and on-device inference

Highlights

Step-by-step reasoning — a thinking mode that works through multi-step problems.
Code generation & review — writes functions and traces bugs across long files.
Multilingual — drafting, translation, and Q&A across languages.
1M context, MoE routing — 158.1B total with modest active compute per token.

What it is good at

The model lists thinking, reasoning, code, and multilingual capabilities, which line up with these jobs.

Step-by-step reasoning — the thinking and reasoning capabilities let it work through math, logic, and multi-step problems before committing to an answer, rather than guessing in one pass.
Code generation and review — the code capability covers writing functions, explaining unfamiliar snippets, and tracing bugs across a long file thanks to the 1,048,576-token context.
Multilingual work — the multilingual capability handles drafting, translation, and Q&A across languages without sending your text to a hosted service.

Running it locally

At 158.1B parameters the full FP8 weights are large, but the MoE routing means active compute per token stays modest. The 1,048,576-token context lets you feed entire codebases or long documents in one go, provided your RAM and VRAM can hold the working set. Grab the weights from the deepseek-ai repository on Hugging Face:

huggingface-cli download deepseek-ai/DeepSeek-V4-Flash

From there you can serve it with Transformers or vLLM, or skip the setup entirely and load DeepSeek-V4-Flash with one click inside Atomic Chat, which manages the download and runtime for you.

License

DeepSeek-V4-Flash is released under the MIT license. That permits commercial use, modification, redistribution, and private deployment, as long as the copyright and license notice stay with the code. It is one of the most permissive licenses available, so you can build on the model without negotiating separate terms.

Desktop

macOS

(M1 or better)

Download

Windows

(x64)

Download

Linux

(x86_64)

Download

Frequently asked questions

DeepSeek-V4-Flash is an open-weight Mixture-of-Experts language model from deepseek-ai, part of the deepseek_v4 family. It has a 158.1B parameter count, ships in FP8, and supports a 1,048,576-token context window. Its listed capabilities are thinking, reasoning, code, and multilingual, and it is built so only some experts activate per token to keep inference efficient.

The full FP8 weights are 158.1B parameters, so you need a machine with substantial memory, typically a high-VRAM GPU setup or a workstation with large unified memory. The MoE design keeps active compute per token lower than the headline size implies, which helps. Atomic Chat handles the download and runtime, so you mainly need enough RAM and VRAM to hold the model and your context.

Yes. The weights are released under the MIT license, and running the model locally through Atomic Chat costs nothing per token. There is no API key or subscription. You only pay for the hardware and electricity to run it on your own machine.

Yes. Once you download the weights with Atomic Chat, the model runs fully on your device with no internet connection required. Prompts and responses stay local, which keeps your data private. You only need a connection for the initial download of the model files.

You can download the weights from the deepseek-ai repository on Hugging Face with huggingface-cli download deepseek-ai/DeepSeek-V4-Flash, then serve them using Transformers or vLLM. The simpler path is to open Atomic Chat and load DeepSeek-V4-Flash with one click, which sets up the download and runtime for you. After that you chat with it directly, offline and on your own hardware.