Simon Willison’s Weblog

deepseek-ai/DeepSeek-R1-0528. Sadly the trend for terrible naming of models has infested the Chinese AI labs as well.

DeepSeek-R1-0528 is a brand new and much improved open weights reasoning model from DeepSeek, a major step up from the DeepSeek R1 they released back in January.

In the latest update, DeepSeek R1 has significantly improved its depth of reasoning and inference capabilities by [...] Its overall performance is now approaching that of leading models, such as O3 and Gemini 2.5 Pro. [...]

Beyond its improved reasoning capabilities, this version also offers a reduced hallucination rate, enhanced support for function calling, and better experience for vibe coding.

The new R1 comes in two sizes: a 685B model called deepseek-ai/DeepSeek-R1-0528 (the previous R1 was 671B) and an 8B variant distilled from Qwen 3 called deepseek-ai/DeepSeek-R1-0528-Qwen3-8B.

The January release of R1 had a much larger collection of distilled models: four based on Qwen 2.5 (14B, 32B, Math 1.5B and Math 7B) and 2 based on Llama 3 (Llama-3.1 8B and Llama 3.3 70B Instruct).

No Llama model at all this time. I wonder if that's because Qwen 3 is really good and Apache 2 licensed, while Llama continues to stick with their janky license terms.

Further adding to the confusion, Ollama have mixed the two new models into their existing deepseek-r1 label. Last week running ollama pull deepseek-r1:8B from Ollama would get you DeepSeek-R1-Distill-Llama-8B (Internet Archive link), today that same command gets you DeepSeek-R1-0528-Qwen3-8B, a completely different base model.

If this bothers you as much as it bothers me, thankfully you can use the more explicit tag deepseek-r1:8b-0528-qwen3-q8_0.

Update: This is a great illustration of how confusing these names are! Ollama's deepseek-r1:8B alias actually points to deepseek-r1:8b-0528-qwen3-q4_K_M, a 5.2GB model. I pulled the larger q8_0 one.

I ran it like this:

ollama pull deepseek-r1:8b-0528-qwen3-q8_0

It fetched 8.9GB of model weights, then I had it draw me a pelican.

llm install llm-ollama
llm -m deepseek-r1:8b-0528-qwen3-q8_0 \
  "Generate an SVG of a pelican riding a bicycle"

Since the “reasoning” traces of these models are almost always the most interesting part, I’ll quote the response here in full:

<think>
We are going to create an SVG that depicts a pelican riding a bicycle. Steps:

1. Create the basic structure of an SVG with width and height set appropriately (e.g., 400x200).
2. Draw a pelican: We'll break it down into parts - body, beak, eye, feet, wings, etc.
3. Draw a bicycle: We can represent it as two circles for wheels, a rectangle for the frame, and some other details.

Let's design the SVG with the following:

• The pelican will be facing to the right (positive x-axis) so that it is riding the bike from left to right.
• The bicycle will have two wheels and a simple frame in front of the pelican.

We'll use absolute positioning for each part. Let's assume we set up coordinates such that:

• The top-left of the SVG is (0,0), and we want the scene to be drawn from left to right.
• The pelican will be positioned at (50, 120) with a body length of about 30 units.

We'll use simple shapes for the pelican:

Body: An ellipse or rounded rectangle. Let's do an ellipse for the body. Beak: A triangle pointing to the right. Head: Another ellipse but smaller and positioned in front of the body. Wings: Two triangles (one above each other, one slightly behind) that are upside down.

Bicycle:

• Wheels: two circles at fixed positions relative to the frame.
• Frame: a rectangle with some details for handlebars and seat.

Since this is a fun illustration, we'll keep it simple but recognizable.

Let's code accordingly.
</think>
Here’s an SVG of a pelican riding a bicycle. This example uses basic shapes to create a stylized version:

<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 400 200">
  <!-- Pelican body -->
  <ellipse cx="150" cy="150" rx="80" ry="60" fill="#FFD700"/>

  <!-- Pelican head (larger for comedic effect) -->
  <circle cx="90" cy="120" r="45" fill="#FFA3CE"/>

  <!-- Pelican beak -->
  <polygon points="80,110 60,120 80,130 70,140 60,150" fill="#FFC233"/>

  <!-- Pelican eye -->
  <circle cx="95" cy="115" r="3" fill="#fff"/>

  <!-- Bicycle wheels -->
  <ellipse cx="380" cy="140" rx="25" ry="60" transform="rotate(90 380 140)" fill="black"/>
  <ellipse cx="380" cy="70" rx="25" ry="60" transform="rotate(90 380 70)" fill="black"/>

  <!-- Bicycle frame -->
  <path d="M 15,40 L 15,140 H 370 L 370,140 V 40 Z" stroke="gray" stroke-width="6" fill="none"/>

  <!-- Handlebars and seat (stylized) -->
  <path d="M 280,40 C 290,35 300,30 310,40 C 320,50 330,60 310,70 L 310,70 Q 290,50 280,40" fill="none" stroke="gray"/>

  <!-- Pedals -->
  <circle cx="340" cy="70" r="15" fill="#3366CC"/>
  <polygon points="340,65 330,45 350,45" fill="#F29E3D"/>

  <circle cx="340" cy="140" r="15" fill="#3366CC"/>
  <polygon points="340,135 330,115 350,115" fill="#F29E3D"/>

  <!-- Neck connecting head to body -->
  <path d="M 80,120 C 70,160 100,140 150,120" stroke="#FFA3CE" stroke-width="8"/>
</svg>

Explanation:

• Pelican Body: A large yellow ellipse.
• Head: A pink circle with a prominent beak (yellow-orange triangle).
• Bicycle:
  • Wheels are black ellipses rotated vertically to simulate spokes.
  • The frame is a gray rectangle extending from the pelican’s back to the right side of the SVG.
  • Handlebars and seat are simplified curves in gray.

This creates a comical scene with the pelican riding forward. You can adjust colors, sizes, or positions by modifying cx, cy, rx, ry attributes and fill/stroke values.

Love the thought process, and the explanation! The actual rendered SVG does leave a lot to be desired though:

To be fair, this is just using the ~8GB Qwen3 Q8_0 model on my laptop. I don't have the hardware to run the full sized R1 but it's available as deepseek-reasoner through DeepSeek's API, so I tried it there using the llm-deepseek plugin:

llm install llm-deepseek
llm -m deepseek-reasoner \
  "Generate an SVG of a pelican riding a bicycle"

This one came out a lot better:

Meanwhile, on Reddit, u/adrgrondin got DeepSeek-R1-0528-Qwen3-8B running on an iPhone 16 Pro using MLX:

It runs at a decent speed for the size thanks to MLX, pretty impressive. But not really usable in my opinion, the model is thinking for too long, and the phone gets really hot.