DeepSeek R1 vs OpenAI o1 vs Sonnet 3.5: Battle of Best LLMs

DeepSeek R1: A Budget-Friendly LLM Rivaling GPT-4 and Claude

Chinese AI innovator DeepSeek has been making waves since the New Year, launching the DeepSeek V3 model (a GPT-4 competitor) and its accompanying mobile app. Their latest offering, DeepSeek R1, is a large language model (LLM) challenging industry leaders at a significantly reduced price. This blog post compares DeepSeek R1 against OpenAI's o1 and Claude Sonnet 3.5, putting its performance claims to the test.

DeepSeek R1: An Overview

DeepSeek R1 is an open-source LLM prioritizing advanced reasoning capabilities. Its unique training methodology leverages reinforcement learning (RL), minimizing reliance on traditional supervised fine-tuning (SFT). This focus on logic, problem-solving, and interpretability makes it well-suited for STEM tasks, coding, and complex Chain-of-Thought (CoT) reasoning. It directly competes with OpenAI's o1 and Claude's Sonnet 3.5. Importantly, DeepSeek R1's API boasts a significantly lower cost—97% cheaper than Sonnet 3.5 and 93% cheaper than o1 (for cache hit input).

Accessing DeepSeek R1

DeepSeek R1 is accessible via the DeepSeek Chat interface (https://www.php.cn/link/9f3ad7a14cd3d1cf5d73e8ec7205e7f1) or its API (https://www.php.cn/link/23264092bdaf8349c3cec606151be6bd). The chat interface requires account creation or login, then selecting "DeepThink." API access requires obtaining an API key from the developer portal and configuring your development environment. The API base URL is: https://www.php.cn/link/aaf9290b7570c56dd784f192425658d4

DeepSeek R1 vs. OpenAI o1 vs. Claude Sonnet 3.5: A Detailed Comparison

Feature	DeepSeek R1	OpenAI o1 Series	Claude Sonnet 3.5
Training Approach	Reinforcement learning (RL), minimal SFT	Supervised fine-tuning (SFT) RLHF	Supervised fine-tuning RLHF
Special Methods	Cold-start data, rejection sampling, pure RL	Combines SFT and RL for general versatility	Focused on alignment and safety
Core Focus	Reasoning-intensive tasks (math, coding, CoT)	General-purpose LLM	Ethical and safe AI, balanced reasoning
Input Token Cost (per million)	.14 (cache hit), .55 (cache miss)	.50–	.45–.60
Output Token Cost (per million)	.19		–
Affordability	Extremely cost-effective	High cost	Moderately priced
Accessibility	Fully open-source (free for hosting/customization)	Proprietary, pay-per-use API	Proprietary, pay-per-use API

Performance Benchmarks: Task-Based Evaluation

The following tasks were used to evaluate DeepSeek R1, OpenAI o1, and Sonnet 3.5, scoring each response from 1-5 (5 being the highest).

• Task 1: Logical Reasoning:
A word problem calculating the number of legs on the floor. None of the models provided a completely correct answer.

• Task 2: Scientific Reasoning:
A physics-based problem involving a laser and mirror. DeepSeek R1 provided the best response with a helpful visualization.

• Task 3: Coding Skills:
Creating an HTML page with a button that changes background color and adds confetti. DeepSeek R1 provided the most functional and integrated solution.

• Task 4: Problem-Solving Skills:
Writing a program to solve a Sudoku puzzle. Sonnet 3.5 provided the most elegant and well-structured code.

(Detailed results and screenshots of each task's output are included in the original article.)

Final Results and Conclusion

While DeepSeek R1 demonstrated strong reasoning capabilities, particularly in scientific reasoning and coding tasks, it wasn't flawless. Occasional syntax errors and slower response times were observed. OpenAI o1 provided detailed explanations, while Sonnet 3.5 offered speed and conciseness. The choice between these models depends on individual needs and priorities. DeepSeek R1's significant cost advantage makes it a compelling option for users with budget constraints.

(The original article's concluding section, including FAQs, is also included in the original response.)

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