Artificial Intelligence 29 Jan, 2025.
DeepSeek has sent the global AI landscape into a tailspin. Apart from disrupting the market caps of major players like OpenAI and Nvidia, DeepSeek has shown just how resource-efficient AI development can be.
DeepSeek created the next big LLM for a mere fraction of the cost as compared to enterprise-scale AI models like Gemini, Claude, Llama, and the one that started this revolution – ChatGPT.
However, you might wonder which LLM is better in 2025 – DeepSeek or ChatGPT.
We have tested both these models to provide a detailed analysis of which LLM reigns supreme and whether ChatGPT’s massive infrastructure keeps it ahead of DeepSeek in terms of model accuracy, reliability, and efficiency.
Read More: How to Build an LLM Like DeepSeek?
DeepSeek vs ChatGPT in 2025 – Comparing Benchmarks
DeepSeek has compared its V3 model with ChatGPT 4o, Llama 3.1, and Claude 3.5 based on numerous benchmarks that calculate its prowess in English language and coding:
| Benchmark | DeepSeek V3 | Llama 3.1 | Claude 3.5 | GPT 4o |
| Architecture | MoE | Dense | – | – |
| # Activated Params | 37B | 405B | – | – |
| # Total Params | 671B | 405B | – | – |
| MMLU (EM) | 88.5 | 88.6 | 88.3 | 87.2 |
| MMLU-Redux (EM) | 89.1 | 86.2 | 88.9 | 88.0 |
| MMLU-Pro (EM) | 75.9 | 73.3 | 78.0 | 72.6 |
| DROP (3-shot F1) | 91.6 | 88.7 | 88.3 | 83.7 |
| IF-Eval (Prompt Strict) | 86.1 | 86.0 | 86.5 | 84.3 |
| GPQA-Diamond (Pass@1) | 59.1 | 51.1 | 65.0 | 49.9 |
| SimpleQA (Correct) | 24.9 | 17.1 | 28.4 | 38.2 |
| FRAMES (Acc.) | 73.3 | 70.0 | 72.5 | 80.5 |
| LongBench v2 (Acc.) | 48.7 | 36.1 | 41.0 | 48.1 |
| HumanEval-Mul (Pass@1) [Coding] | 82.6 | 77.2 | 81.7 | 80.5 |
| LiveCodeBench (Pass@1-COT) [Coding] | 40.5 | 28.4 | 36.3 | 33.4 |
| LiveCodeBench (Pass@1) [Coding] | 37.6 | 30.1 | 32.8 | 34.2 |
| Codeforces (Percentile) [Coding] | 51.6 | 25.3 | 20.3 | 23.6 |
| SWE Verified (Resolved) [Coding] | 42.0 | 24.5 | 50.8 | 38.8 |
| Aider-Edit (Acc.) [Coding] | 79.7 | 63.9 | 84.2 | 72.9 |
Testing DeepSeek vs ChatGPT for Different Use Cases
Now that we’ve discussed benchmarks, let’s see how these AI models perform in real life:
Writing
When it comes to writing assistance, both DeepSeek and ChatGPT can help organize information and ideas into structured documents. They’re able to gather key points and put them into a helpful format.
For example, when asked to summarize the careers of legendary English football players for a blog post, both chatbots could produce brief overviews of the top players’ achievements. DeepSeek even caught non-English greats like Wales legend Ryan Giggs who played for Manchester United. Its final post had a smooth flow and structure. ChatGPT also named the main English legends accurately in its summarization.
Overall, ChatGPT may have slightly more creative writing flair at this stage. But DeepSeek follows instructions very well for an AI assistant. Its technical accuracy and precision are also appreciated. For business use cases, DeepSeek can deliver orderly drafts and templates on demand across many topics.
Read More: New Custom ChatGPT Builder – Opportunities for Businesses
Programming
In coding tests, DeepSeek shows smart logic in how it tries to tackle problems. For example, when asked to write code for a basic calculator app, it methodically recalled formulas and attempted fixes when it ran into syntax issues. This hands-on effort at reaching solutions step-by-step impressed programmers and developers.
ChatGPT, on the other hand, directly provided working calculator code without needing trial-and-error fixes. However, some users noticed its calculator interface design lacked certain touches – like a clear button for the display – compared to DeepSeek’s.
So there seems to be an emerging pattern here: ChatGPT for versatility and creative problem-solving versus DeepSeek for rigorous technical precision. Both have their strengths among builders and engineers.
Read More: Is Devin AI The End (Or Future) Of Coding?
Brainstorming
Need fresh ideas for a fictional tale? Both AI assistants can suggest creative prompts on demand to kickstart writing sessions.
When asked to help ideate children’s story concepts about a girl living on the moon, ChatGPT provided multiple fun premises that could form the basis for plotlines and adventures. The ideas contained original worldbuilding and character details.
DeepSeek took a notably different track here – it directly wrote out a complete short children’s story called “Luna and the Girl Who Chased Stars” rather than just offering initial prompts.
So we see a by-now familiar pattern emerge again: ChatGPT rapidly fires quick-starting thoughts and ideas, while DeepSeek travels further down one path to develop an initial concept into a more finished product. Both approaches have real merit for writers facing blank pages or creative blocks.
Read More: 150+ Best Writing Apps and Tools for Writers
Math
Submit a math word problem or equation to these AIs, and more often than not they can attempt working through solutions step-by-step to get accurate answers. Their logic chains and processes are remarkably sound for an AI assistant.
However, ChatGPT has a tendency to define more symbols, terminology, and methods upfront in its explanations before solving. This makes its walkthroughs seem more textbook-like, which educators say gives ChatGPT the edge for supporting lessons and student learning.
DeepSeek operates more conversationally in tackling math problems, getting right to the problem-solving without as much vocabulary scaffolding as ChatGPT. So it becomes a choice between more structured explanations versus raw computation power.
Read More: How to Build AI Agents – A Comprehensive Guide
Reasoning
Among their most human-like talents so far, both DeepSeek and ChatGPT can mimic chains of analysis for decision-making when presented with constraints and trade-offs to weigh. By thinking through the pros and cons of various choices, they simulate internal reasoning that applies logic and critical thinking.
For example, when advising a user on purchasing laptops given a tight budget cap, DeepSeek discusses ultrabook versus gaming machine considerations out loud. It voices factors like performance needs versus costs in a stream-of-consciousness manner, demonstrating organized logic flow.
Similarly, when given the laptop purchasing scenario, ChatGPT also reasons about the merits of different types of machines and how to maximize value while accounting for budget limitations.
This ability to think aloud while rationalizing through decisions reveals AI systems reaching new milestones in mental capacity previously unattainable. The simulation of human-style contemplation hints at a bright future powered by artificial intelligence.
Read More: Is Google’s New Gemini AI Better than ChatGPT?
Final Thoughts
As DeepSeek, ChatGPT, and other LLMs continue evolving at a rapid clip, they’re bound to keep closing gaps while racing ahead in new specialties over time. From creative expression to precision calculations and beyond, the natural language mastery we’re witnessing has a vast upside for expanding human knowledge potential.
And with innovators worldwide now leapfrogging benchmarks and spreading ideas faster, the outlook truly glistens across this technology area as the lightbulbs keep lighting brighter every season in labs near and far. Both average consumers and enterprises hungry for solutions stand to win big from the ascent of tools like DeepSeek and ChatGPT.
No matter who wins in the DeepSeek vs ChatGPT battle, one thing’s certain – building an enterprise-grade LLM is achievable for every AI startup, especially when partnering with a trusted AI development company like Cubix.
We have the expertise, resources, and talent needed to accelerate your LLM development initiatives.
Contact our representatives and we’ll see how we can drive AI product innovation for your business.
Mohammad Azeem
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