DeepSeek-V2-236B-Chat

Name: DeepSeek-V2-MoE-236B-Chat
Author: DeepSeek-AI

Chat modelDeepSeek VDeepSeek V2

DeepSeek-V2-MoE-236B-Chat

Release date: 2024-05-06Updated: 2024-06-07Views: 605

Live demoGitHub Hugging Face Compare

Parameters

236B

Context length

128K

Multilingual

Supported

Reasoning ability

No data

DeepSeek-V2-MoE-236B-Chat is an AI model published by DeepSeek-AI, released on 2024-05-06, for Chat model, with 236B parameters, and 128K context length, requiring about 472GB storage, with a 54.81 score on MMLU Pro.

Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology

DeepSeek-V2-236B-Chat

Model basics

Reasoning traces

No data

Thinking modes

Thinking modes not supported

Context length

128K tokens

Max output length

No data

Model type

Chat model

Modality (in / out)

No data

Release date

2024-05-06

Model file size

472GB

MoE architecture

Total params / Active params

236B / Not applicable

Knowledge cutoff

No data

DeepSeek-V2-236B-Chat

Open source & experience

Code license

MIT License

Weights license

DeepSeek License Agreement- Commercial use permitted

GitHub repo

github.com/deepseek-ai/DeepSeek-V2

Hugging Face

huggingface.co/deepseek-ai/DeepSeek-V2-Chat

Live demo

N/A

DeepSeek-V2-236B-Chat

Official resources

Paper

N/A

DataLearnerAI blog

N/A

DeepSeek-V2-236B-Chat

API details

API speed

No data

No public API pricing yet.

DeepSeek-V2-236B-Chat

Benchmark Results

DeepSeek-V2-236B-Chat currently shows benchmark results led by MMLU Pro (133 / 176, score 54.81), Aider-Polyglot (52 / 59, score 17.80). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.