What’s New and Why It Matters

DeepSeek’s most recent update, R1-0528, may be called a “minor trial upgrade,” but it makes major leaps. With considerable advancements in reasoning, code generation, and dependability, R1-0528 places DeepSeek as an open-source contender to Gemini 2.5 Pro. It even approaches OpenAI’s o3 and o4-mini in terms of code benchmarks. In this blog, we’ll explore the features of this upgrade and provide hands-on comparisons between DeepSeek R1 and the new R1.1.

What is DeepSeek R1-0528?

DeepSeek R1-0528, also called DeepSeek R1.1 is a next-generation, open-source large language model (LLM) released by DeepSeek. This new model represents a new generation of AI systems going head-to-head with world-leading proprietary models by the likes of OpenAI and Google.

DeepSeek R1-0528 is particularly focused on reasoning, code generation, and complex problem-solving abilities. This makes it a game-changing resource for researchers, developers, and businesses seeking to leverage powerful AI systems, without relying on a closed ecosystem and proprietary, subscription-based AI models.

Want to learn more about the DeepSeek R1 model? Click here.

What’s New in DeepSeek R1-0528?

DeepSeek R1 came out earlier this year with a bag of innovative features. Now, with its latest update, DeepSeek R1-0508, the open-source model has become bigger and better.

Some of its upgraded features are:

• Massive Parameter Scale: It is trained on a whopping 671 billion parameters. This opens up a lot of possibilities for powerful and efficient processing.
• Fully Open-Source: It is a fully open-source model, allowing for transparency and community-driven upgrade potential.
• Smarter Reasoning: The model achieves improvements in reasoning capabilities, leading to better logic and problem-solving.
• Better Code Generation: It provides better accuracy and efficiency in code generation, coming closer to the leading closed-source models.
• Enhanced Reliability: It is also more reliable and consistent with responses.
• Longer Thinking: The model is capable of thinking for longer durations over complex problems, showcasing a much better performance than its previous version.

DeepSeek R1-0528: Performance Benchmarks

The earlier version of DeepSeek R1 blew the world away with its performance. It gave tough competition to all the popular models at the time and proved that open-source models can be at par with closed-source ones. Now, DeepSeek R1.1 also proves to be quite similar in its impact!

Let’s look at the performance of DeepSeek R1.1 against the top models on the composite LLM performance score, which is aggregated from benchmarks like MMLU, HumanEval, GSM8K, BBH, TruthfulQA, etc.

With a median of 69.45, DeepSeek R1 – 0528 performs reliably across a wide range of tasks (e.g., reasoning, coding, math, etc.). It delivers near Claude-level median performance at a fraction of the cost, making it one of the best value-for-money models in this list. It outperforms Gemini 2.5 Pro and even Claude Sonnet 4 in consistency while costing 5x–7x less.

DeepSeek R1-0528 vs DeepSeek R1: Hands-on Comparison

Now let’s get to a real-world comparison of DeepSeek R1 and R1-0528 on reasoning, code generation, and reliability. We’ll be testing out both models on 3 different tasks to see how they perform and find out if the new upgrade actually does better.

Task 1: Construct a User Interface Similar to Instagram

Both models will be tasked with building an HTML page that mimics the Instagram design. This will test their code generation quality, structural understanding of UI, and correctness of logic in frontend development.

Input Prompt: “Create a responsive HTML and CSS layout that looks like Instagram’s main feed page. It should include:

A fixed top navigation bar with the Instagram logo on the left, a search bar in the center, and navigation icons (home, messages, explore, notifications, profile) on the right.

A sidebar on the left for navigation with icons and labels similar to Instagram (Home, Search, Explore, Reels, Messages, Notifications, Create, Profile).

A main feed in the center showing several post cards. Each post should include:

• A user avatar and username at the top
• An image
• Action icons (like, comment, share, save)
• A like count
• A caption
• A comment section

A sidebar on the right with suggestions for “People you may know.”

Output by DeepSeek R1-0528:

Output by DeepSeek R1:

Output Comparison

DeepSeek R1-0528 showed smoother rendering, much better UI responsiveness, and somewhat more aligned frame synchronization with each other. The image quality seems slightly sharper, too, probably because of improved internal sampling or export methods.

DeepSeek R1’s transitions and rendering seem a bit slower in comparison. It has minimal frame lags or delays regarding processing, particularly in action-dense areas or transitioning frames.

These observations imply that the R1-0528 update perhaps includes improvements to performance and visual fidelity.

Task 2: Planning a Trip to India

Each model will be tasked with curating a cost-effective trip to India. They will have to include an itinerary, along with costs and rationale. This will test their planning skills, knowledge of the real world, as well as their ability to create structured and actionable content.

Input Prompt: “Plan a 3-day trip to India focused on tech, food, and history with the price of expenses mentioned.“

Output by DeepSeek R1-0528 (truncated):

3-Day India Trip: Delhi & Agra – Tech, Food & History Adventure
(Budget: Mid-Range Solo Traveler) 💰 Total Cost: ~₹25,000–30,000 ($300–360 USD)
Prices cover food, transport, entry fees, and accommodation. Flights not included.
Day 1: Delhi – History & Food
Focus: Mughal/Colonial History + Street Food
Accommodation: Mid-range hotel (Karol Bagh/Aerocity) – ₹2,500/night

• Morning (History):
• Red Fort (UNESCO Site): Explore Mughal architecture. (Entry: ₹500)
• Jama Masjid: India’s largest mosque. (Free entry; ₹300 for tower access)
• Lunch (Food): Karim’s (Old Delhi) – Iconic Mughlai kebabs & biryani. (₹400)
• Afternoon (History):
• Raj Ghat: Gandhi’s memorial. (Free)
• Humayun’s Tomb (UNESCO Site): Pre-Taj Mughal marvel. (Entry: ₹600)
• Dinner (Food): Paranthe Wali Gali – Fried breads with fillings. (₹200)
• Evening: Walk through Chandni Chowk market.

Daily Cost: ₹4,500 (hotel, food, transport, entries)

Output by Deepseek R1 (truncated):

Here’s a well-balanced 3-day trip plan for India covering tech hubs, historical sites, and food experiences, with estimated expenses (in USD and INR for easy reference).

Day 1: Bangalore – The Silicon Valley of India
Theme: Tech + Modern Indian Food

Morning: Tech Exploration
Visit Infosys Campus or Google Office (Outer View)– See India’s IT hub (no entry inside without permission).  
Indian Institute of Science (IISc) – Premier research institute (free entry, but check visiting hours).  
Visvesvaraya Industrial & Technological Museum – Interactive tech exhibits (Entry: $2 / ₹150).

Cost: ~$5 / ₹400

Afternoon: Food & Culture  
Lunch at Mavalli Tiffin Rooms (MTR) – Famous for South Indian meals (~$8 / ₹600).  
Commercial Street Shopping – Quick souvenir stop (optional).

Evening: Modern Bangalore  
UB City Mall – High-end tech & luxury brands.  
Dinner at Toit Brewpub – Craft beer & fusion food (~$15 / ₹1,200).

Total Day 1 Cost: ~$30 / ₹2,500  

You can view the complete output of both models here.

Output Comparison

Both models show strong skills in planning and generating structured content. However, there are differences in the style and depth of their travel planning.

DeepSeek R1-0528 plans a more cohesive travel experience using a focused location (Delhi-Agra) to minimize travel overhead. At the same time, it adds richness with experiences like tech-themed food, marble workshops, and interpretations of contemporary and modern history around culinary traditions.

DeepSeek R1 covers a few major cities – Bangalore, Delhi, and Hyderabad, which certainly provides a breadth of exposure. However, it comes at a much larger cost and logistical management of experiences… it’s more ambitious for sure than DeepSeek R1-0528, but less viable as a goal of being “cost-effective.”

Task 3: Logical Reasoning Task

Both models will be presented with a logic puzzle in physics so we can assess their problem-solving skills, deductive reasoning skills, and clarity of answer explanations.

Input Prompt: “You have 3 light bulbs in a room and 3 switches outside. How do you determine which switch controls which bulb if you can only enter the room once?”

Output by DeepSeek R1-0528:

To determine which switch controls which light bulb with only one entry into the room, follow these steps:

• Label the three switches outside the room as Switch 1, Switch 2, and Switch 3 for reference.
• Turn on Switch 1 and leave it on for about 5 minutes.
• After 5 minutes, turn off Switch 1 and immediately turn on Switch 2.
• Enter the room right after turning on Switch 2 and observe the state of each bulb:
• If a bulb is on, it is controlled by Switch 2.
• If a bulb is off but warm to the touch, it is controlled by Switch 1 (since it was on long enough to heat up but is now off).
• If a bulb is off and cold to the touch, it is controlled by Switch 3 (since it was never turned on).

Why this works:

• By using the time delay with Switch 1, you allow the bulb to heat up. When you turn it off, it remains warm for a short period.
• Turning on Switch 2 immediately before entering ensures that its bulb is on.
• Switch 3 remains off, so its bulb is off and cold.
• This method leverages both the on/off state and the temperature of the bulb as indicators, allowing you to identify all three with a single entry.

Note: This solution assumes the light bulbs are incandescent and generate noticeable heat when on. If the bulbs are LED or another type that does not produce heat, this method may not work, but traditional puzzles assume heat-generating bulbs.

Output by DeepSeek R1:

The Classic Light Bulb Puzzle: Solution

Problem Statement:  

You have 3 switches outside a room and 3 bulbs inside the room. You can turn the switches on or off, but you can only enter the room once to inspect the bulbs. How do you determine which switch controls which bulb?

Step-by-Step Solution:

1. Label the switches for clarity (e.g., Switch A, Switch B, Switch C).
2. Turn on Switch A and leave it on for about 5 minutes.  

   – This duration allows the bulb controlled by Switch A to heat up (incandescent bulbs warm up noticeably).

3. After 5 minutes, turn off Switch A and immediately turn on Switch B.  

   – Now:

     – Switch A: Off (but bulb is warm)

     – Switch B: On (bulb is lit)

     – Switch C: Off (bulb is cold and off)

4. Enter the room to observe the bulbs:

   – Bulb that’s ON → Controlled by Switch B (since it’s currently receiving power).

   – Bulb that’s OFF but WARM → Controlled by Switch A (was recently on and heated up).

   – Bulb that’s OFF and COLD → Controlled by Switch C (was never turned on).

 Key Insight:

• Uses heat (from the bulb being on) and light (current state) as indicators.
• Works only with incandescent bulbs (not LEDs or CFLs, which don’t heat up as noticeably).

Summary Table:

This method reliably maps all 3 switches to their bulbs in a single room entry.

Output Comparison

Both models accurately identify the puzzle solution using the standard approach of using heat and light to eliminate switches. However:

DeepSeek R1-0528 provides a more concise, readable, and efficient answer, where it highlights practical steps and includes a helpful note about bulb type compatibility.

DeepSeek R1 offers a more instructional, formal organization of text with helpful headings, a summary table, and slightly more elaboration on all of the decision steps.

Result Overview

DeepSeek R1-0528 showed significant performance enhancements compared to R1 across all tasks. In trip planning, R1-0528 provided a more useful cost-effective, and organized itinerary. The video output evidenced a smoother and more polished output that likely implies improved rendering. In the logic puzzle activity, both solved the task correctly, however, R1-0528 also gave a more brief and natural description. Overall, R1-0528 is more usable, flexible/ relevant, and grounded for day-to-day tasks.

Conclusion

DeepSeek R1-0528 is a considerable advancement in the democratization of advanced AI technologies. It combines state-of-the-art performance with open-source availability to challenge proprietary models with its compatibility and ease of use, while allowing more individuals to leverage cutting-edge AI for research, development, and business use. Whether you are a developer who wants to build intelligent applications, a researcher eager to explore novel AI frontiers, or a business wanting cost-effective and innovative solution providers, DeepSeek R1-0528 is a uniquely focused and capable platform for the future.