DeepSeek Model 1
Visualization
Redefining how AI thinks, starting with R1. We help you understand the hardcore architectural innovations behind DeepSeek Model 1 through interactive visualizations.
Why DeepSeek Model 1?
DeepSeek Model 1 (represented by R1) marks a turning point in Artificial General Intelligence (AGI): models are no longer just predicting the next token, but learning to "think". DeepSeek achieved this breakthrough through pure reinforcement learning, proving that reasoning can emerge without explicit human instruction.
DeepSeek is a top-tier AI research lab known for its open-source spirit and extreme efficiency. DeepSeek Model 1 not only rivals closed-source giants (like o1) in performance but, more importantly, reveals the underlying technologies like MLA, MoE Load Balancing, and mHC that make DeepSeek's innovations possible for everyone.
def solve_agi():
# Initialize Model 1 (R1)
vision = "Emergent Reasoning"
strategy = "Pure RL"
innovation = ["MLA", "DeepSeekMoE"]
return AGI
Foundations of Model 1
How does DeepSeek Model 1 (R1/V3) achieve extreme inference efficiency while maintaining high performance?
MLA
Multi-Head Latent Attention. Compresses KV Cache by 90%, enabling massive context windows.
DeepSeekMoE
Fine-grained Mixture of Experts. Introduces Shared Experts for better knowledge retention.
MTP
Multi-Token Prediction. Predicts multiple future tokens at once, speeding up training and inference.
FP8 Training
Full FP8 mixed-precision training. Doubles computation speed without accuracy loss.
Road to Model 1
Every step of DeepSeek has converged into the breakthrough of Model 1.
DeepSeek Coder
Not just code completion, but demonstrating powerful capabilities in code logic reasoning. Established the 'code data enhances general reasoning' route.
DeepSeek MoE
Proposed Fine-grained MoE and Shared Experts mechanisms, solving the knowledge redundancy and load imbalance problems of traditional MoE.
DeepSeek-V2
Introduced MLA (Multi-Head Latent Attention), significantly reducing KV Cache memory usage and slashing long-context inference costs.
DeepSeek-V3
The strongest open-source MoE model currently. Features Auxiliary-Loss-Free Load Balancing, Multi-Token Prediction (MTP), and extreme FP8 training efficiency.
DeepSeek Model 1 (R1)
A Milestone. Incentivizing reasoning capabilities through Pure RL. Adopts GRPO algorithm, eliminating the Critic model, with performance rivaling OpenAI o1.
DeepSeek-OCR
"Contexts Optical Compression". Exploring visual modality as an efficient compression medium for text. A picture is worth a thousand words, significantly reducing token consumption for long contexts.
Core Papers
DeepSeek Model 1 (R1): Reasoning
How does Model 1 learn to 'think'? Revealing the secret of reasoning emergence through pure reinforcement learning (GRPO). No massive labeled data needed, the model learns to self-correct, reflect, and perform long chain-of-thought.
DeepSeek-V4 (Upcoming)
~1T parameters, 1M context window, NSA sparse attention, Engram memory, and Sparse FP8 decoding. The next frontier.
Math-V2
It doesn't just solve; it checks. Discover how 'Self-Verification' enables Gold-Medal level reasoning.
DeepSeek-OCR
Optical Context Compression. Using visual modality to compress text tokens by over 10x.
DeepSeek-V3 Technical Report
Unveiling Auxiliary-Loss-Free Load Balancing, Multi-Token Prediction (MTP), and cost-effective FP8 training.
mHC: Taming Hyper-Connections
How to make models wider without collapsing? Understanding Manifold-Constrained Hyper-Connections.
DualPipe: Pipeline Parallelism
Bidirectional pipeline scheduling that overlaps computation with communication, achieving ~50% bubble reduction.
Why Focus on Model 1?
We transform boring academic PDFs into vivid interactive experiences that make DeepSeek's research accessible to everyone.
Beginner Friendly
No complex math formulas. We use easy-to-understand analogies (like 'dictionary lookup', 'taming wild horses') to explain the core concepts behind DeepSeek's innovations.
Interactive Simulation
Don't just watch, try it! Personally adjust parameters and observe how DeepSeek's architectural innovations work in real-time. Get an intuitive feel for how DeepSeek models process information.
Cutting Edge
Follow the DeepSeek team's arXiv papers immediately. Here, you can not only see DeepSeek's code but also understand the architecture diagrams behind each DeepSeek breakthrough.
Model 1 Ecosystem
Thanks to the open-source community, you can run DeepSeek models anywhere on any platform.