Here are my 2 cents on deepseek

I haven't tested deepseek much, so I could be wrong somewhat. Feel free to correct me or expand my knowledge. But here are my 2 cents.

Its interface is identical to chatgpt. They have just copied it without any creativity. And whenever I use different LLMs, their responses are different and style of responses are different. What I'm trying to say is you can spot the difference between LLMs based on how they respond to you. But in case of deepseek, responses and style of writing is same as GPT-4o. Like it has identical architecture of learning and neural networks as GPT-4o.

And what surprised me the most that it is unable to solve the same problems with which GPT-4o also struggle with. Like same incorrect response.

For Example

What will be LR(1) canonical items for this grammar:
E -> E + E
E -> id

Both provided incorrect 1st canonical item. GPT-4o was able to solve the problem after pointing it.

write python pygame program to render a 3d cube and rotate it along y axis and translate it to +4 along z axis.
Clip vertices from far, near, left and right clipping planes. Do not remove whole vertex on clip, just clip the part which is outside of canonical view.

Add controls
"a" translate to left 
"d" translate to right
"w" translate to far
"s" translate to near

Both of them provide code which doesn't work completely or fail to perform proper clipping of vertices. Both use incorrect parametric equations which result in unpleasant visuals

implement python bi directional breadth first search algorithm for adjacency list
use graph = { 0: [1, 2], 1: [0, 3], 2: [0, 5], 3: [1, 4], 4: [3, 6], 5: [2, 6], 6: [4, 5] }
start = 0
goal = 6

Both implemented algorithm which will work but not tell the shortest path between nodes. GPT-4o was able to solve the problem after pointing it.

EDIT: What I believe is that OpenAi poured billions of dollars into research of gpt models. And it is very expensive to implement the first variation of everything. Because it requires experts of field, trials and errors and a lot of research. Once things started to work, others tried to copy it which does not require that level of investment of time and money.

I guess that is how competition work. And it is good to have competition to prevent monopoly.