DeepSeek R1 Zero
DeepSeek R1 Zero is a research model trained exclusively through reinforcement learning on reasoning tasks, with no supervised fine-tuning (SFT) phase applied after pretraining. This makes it methodologically notable: it demonstrates that chain-of-thought reasoning and self-reflection behaviors can emerge from RL alone, without curated human demonstrations.
Because it bypasses SFT, R1 Zero exhibits raw RL-driven reasoning patterns that differ from standard instruction-tuned models — sometimes verbose or unusual in style, but capable of solving complex math and logic problems. It serves as the research baseline from which the SFT-refined DeepSeek R1 models derive, and is primarily of interest for studying emergent reasoning behaviors rather than production deployment.
Key Features
Reasoning capability developed entirely via reinforcement learning, no SFT
Emergent chain-of-thought and self-verification behaviors
Strong performance on mathematical and logical reasoning benchmarks
Transparent research artifact useful for studying RL-trained reasoning
Foundation architecture for the full DeepSeek R1 model family
Ideal Use Cases
Research into emergent reasoning from reinforcement learning
Mathematical problem solving and proof exploration
Logical deduction tasks where step-by-step reasoning is required
Baseline comparison for evaluating the impact of supervised fine-tuning on reasoning
Example Prompts for DeepSeek R1 Zero
Technical Specifications
| Provider | DeepSeek |
| Category | Reasoning |
| Modality | Text -> Text (reasoning) |
Frequently Asked Questions
Try DeepSeek R1 Zero now
Start using DeepSeek R1 Zero instantly — 100 free credits, no credit card required. Access 750+ AI models through one platform.