DeepSeek-R1

Free

First-generation reasoning models from DeepSeek.

FreeFree tier

Type

Open Source

Company

DeepSeek

Visit Website GitHub (38 stars)

About DeepSeek-R1

DeepSeek-R1 is a first-generation reasoning model from DeepSeek, trained via large-scale reinforcement learning. The family includes DeepSeek-R1-Zero, which is trained purely through reinforcement learning without supervised fine-tuning, and DeepSeek-R1, which incorporates cold-start data before reinforcement learning to enhance reasoning performance and readability. DeepSeek-R1 achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks. The model demonstrates self-verification, reflection, and long chain-of-thought generation. DeepSeek has also open-sourced distilled versions of the model (1.5B to 70B parameters) based on Llama and Qwen, enabling smaller models to achieve strong reasoning capabilities.

Key Features

Trained via large-scale reinforcement learning without supervised fine-tuning (DeepSeek-R1-Zero)

Incorporates cold-start data before reinforcement learning (DeepSeek-R1)

Achieves performance comparable to OpenAI-o1 on math, code, and reasoning tasks

Open-sourced models including DeepSeek-R1-Zero, DeepSeek-R1, and six distilled checkpoints (1.5B to 70B) based on Llama and Qwen

Supports distillation of reasoning patterns into smaller models for better performance than RL-only small models

Exhibits self-verification, reflection, and long chain-of-thought generation

Pros & Cons

Pros

First open research to validate reasoning capabilities can be incentivized purely through RL without SFT
Performance comparable to OpenAI-o1 across multiple benchmarks
Open-source with multiple model sizes to suit different computational budgets
Distillation enables smaller models to achieve state-of-the-art results for their size
Demonstrates advanced reasoning behaviors like self-verification and reflection

Cons

DeepSeek-R1-Zero suffers from issues like endless repetition, poor readability, and language mixing
Training may require significant computational resources (not specified, but implied by scale)
Distilled models, while strong, may not match the full performance of the largest model

Best For

Mathematical reasoning and problem-solvingCode generation and understandingGeneral complex reasoning tasksResearch and development of reasoning capabilities via distillation

FAQ

What is DeepSeek-R1?

DeepSeek-R1 is a first-generation reasoning model developed by DeepSeek, trained with reinforcement learning and cold-start data, achieving performance comparable to OpenAI-o1 across math, code, and reasoning tasks.

What is DeepSeek-R1-Zero?

DeepSeek-R1-Zero is a model trained purely via large-scale reinforcement learning without supervised fine-tuning, demonstrating reasoning capabilities but facing challenges like poor readability and language mixing.

Are the models open source?

Yes, DeepSeek has open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and six distilled models based on Llama and Qwen, ranging from 1.5B to 70B parameters.