Introduction & Features
- Version: DeepSeek V3
- Performance: 3x faster than its predecessor, V2
- APA Compatibility: Fully compatible
- Open Source Model: Competes with Claude 3.5 Sonnet and surpasses Claude 30 Sonnet
- Model Scale: A 67.1B Mixture of Experts (MoE) model with 37B active parameters
- Training Data: Trained on 14 trillion high-quality tokens
- Cost-effectiveness: One of the most cost-efficient models, notably before February 8th
Performance Comparison
- Math Benchmark: DeepSeek scores 90, outperforming GPT-40’s 74.6.
- Language Understanding: Excels across multiple benchmark tests, showing superior comprehension and reasoning.
Architecture & Technology
- Base Architecture: Built on Transformer blocks with a Mixture of Experts (MoE) design.
- Attention Mechanism: Features multi-head latent attention, supporting up to 128,000 tokens.
- Memory Capability: Exceptional memory retention for long sequences, ensuring no detail is forgotten.
Programming Tests
Python Tests
- Tackles challenging problems such as unit matrix generation, LCM, Faray sequence, and ECG sequence.
- Results: DeepSeek performs exceptionally, resolving errors and passing most expert-level tests with ease.
JavaScript Tests
- Handles advanced challenges like the Josephus problem.
- Results: DeepSeek delivers outstanding performance, showcasing its programming expertise.
Logic & Reasoning Tests
- Logic Problems: Tasks like counting the number of “O”s in “strawberry.”
- Reasoning Ability: Successfully solves a series of complex logical problems, demonstrating strong analytical skills.
Autonomous Behavior Tests
- Agent Behavior: Tested using the Praise AI package.
- Task Example: Creating a movie script about a lost cat.
- Results: Agents collaborate effectively, utilizing search tools and completing tasks autonomously.
Misdirection Tests
- Scenario Test: Runway trolley problem.
- Results: DeepSeek shows limitations in handling moral judgments, indicating areas for future improvement.
Summary
- DeepSeek V3 matches Claude 3.5 Sonnet and outperforms it in specific benchmarks.
- It is open source, cost-effective, and excels in expert-level programming and logical reasoning tasks.
- While it demonstrates strong autonomous behavior capabilities, it faces challenges in misdirection scenarios.