DeepSeek
LLM ModelsFreemium

DeepSeek

Disruptively priced open-weight reasoning models (R1) and general-purpose LLMs (V3). Features chain-of-thought reasoning comparable to o1 at a fraction of the cost.

DeepSeek offers high-performance open-weight models like the reasoning-focused R1 and efficient V3. Known for being up to 90% cheaper than GPT-4 while matching reasoning capabilities in coding and math.

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Overview

DeepSeek: The Open-Weight Reasoning Powerhouse

DeepSeek has disrupted the AI landscape with DeepSeek-R1, an open-weight reasoning model that rivals OpenAI's o1-preview performance in coding and mathematics at a fraction of the cost.

Key Models

1. DeepSeek-R1 (Reasoning)

  • Chain-of-Thought: Uses advanced reinforcement learning to "think" before answering, excelling at complex logic and coding tasks.
  • Performance: Matches top-tier closed models (GPT-4o, Claude 3.5) on benchmarks like AIME and MATH-500.
  • Open Weights: Fully open MIT license, allowing local deployment and fine-tuning.

2. DeepSeek-V3 (General Purpose)

  • Efficiency: Uses Multi-Head Latent Attention (MLA) and Mixture-of-Experts (MoE) for extreme inference speed.
  • Cost: API costs are approximately 90% lower than comparable frontier models ($0.14/1M input tokens).
  • Context: Supports up to 128k context window with efficient caching.

Features

  • Context Caching: drastically reduces costs for repetitive tasks.
  • Local Deployment: Run R1 locally using Ollama or vLLM.
  • API Access: Fully compatible OpenAI-format API for easy integration.

Pricing

  • API: Extremely low cost (e.g., $0.14/1M input tokens for V3).
  • Open Weights: Free to download and use commercially (MIT License).

Use Cases

Code Generation

Natural Language Processing

Reasoning

Data Analysis