What is the difference between DeepSeek R1 and GPT-5.4 Mini?

DeepSeek R1 is developed by DeepSeek while GPT-5.4 Mini is developed by OpenAI. DeepSeek R1 has a 128K token context window vs GPT-5.4 Mini's 400K. You can compare their actual outputs across 41 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek R1 or GPT-5.4 Mini?

It depends on your use case. DeepSeek R1 and GPT-5.4 Mini each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 41 challenges so you can judge which fits your needs best.

How much does DeepSeek R1 cost compared to GPT-5.4 Mini?

DeepSeek R1 costs $0.55/M input tokens and GPT-5.4 Mini costs $0.75/M input tokens. DeepSeek R1 is $0.20/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare DeepSeek R1 and GPT-5.4 Mini on Rival?

This page shows a side-by-side comparison of DeepSeek R1 and GPT-5.4 Mini across shared challenges. You can vote on which model produced the better output, and Pro users can create custom challenges to test both models with their own prompts.

Rival

Updated Mar 17, 2026

DeepSeek R1vsGPT-5.4 Mini

36 fights queued

Why DeepSeek R1?

2x cheaper overall$0.55/M in · $2.19/M out

Why GPT-5.4 Mini?

3.1x more context400K

14 months newerMar 2026

DeepSeek R1GPT-5.4 Mini

Input price

$0.55/M

$0.75/M

Output price

$2.19/M

$4.50/M

Context

128K

400K

Released

Feb 2025

Mar 2026

Favorites

DeepSeek R1GPT-5.4 Mini

Movie

The Godfather

19728.7

The Godfather

19728.7

Album

The Dark Side of the Moon

Pink Floyd

Kid A

Radiohead

Book

Pride and Prejudice

Jane Austen

Pride and Prejudice

Jane Austen

City

Kyoto

Japan

Kyoto

Japan

Game

The Legend of Zelda: Ocarina of Time

Adventure, Action4.4

The Legend of Zelda: Breath of the Wild

Adventure, Action4.5

6 / 36

Estimate Complexityreasoning

Tests an AI's ability to make educated estimates based on technical knowledge

DeepSeek R1

Deepseek · Feb 2025text

Nothing here. The model returned empty. We stared at it for a while.

Try this prompt

GPT-5.4 Mini

Openai · Mar 2026text

A reasonable back-of-the-envelope estimate for training GPT-3 is about 3 × 10²³ FLOPs total, with maybe a factor-of-2 uncertainty depending on what you count and the exact training setup.

Here’s the reasoning step by step.

1) Use the model size and token count

GPT-3’s largest widely cited version has about:

175 billion parameters = 1.75 × 10¹¹ parameters
Trained on roughly 300 billion tokens = 3 × 10¹¹ tokens

2) Estimate FLOPs per token for training

For a transformer, a rough rule of thumb is:

Forward pass + backward pass costs on the order of 6 × number of parameters FLOPs per token

Why 6?

Forward pass: roughly 2 FLOPs per parameter-use is a common crude estimate
Backward pass: roughly 2–4× the forward cost
So total training cost per token is often approximated as about 6P

Thus:

[ \text{FLOPs per token} \approx 6 \times 1.75 \times 10^{11} = 1.05 \times 10^{12} ]

So each token costs about 1 trillion FLOPs.

3) Multiply by the number of training tokens

[ (1.05 \times 10^{12}) \times (3 \times 10^{11}) = 3.15 \times 10^{23} ]

So the total training compute is about:

[ \boxed{3 \times 10^{23}\ \text{FLOPs}} ]

4) Sanity check

This scale is plausible because GPT-3 was famously extremely expensive to train, and 10²³ FLOPs is in the right ballpark for a model of that size trained on hundreds of billions of tokens.

5) Caveats

This is an estimate, not an exact number, because it depends on:

whether you count only dense matrix ops or also overhead
optimizer cost
attention cost vs. MLP cost
sequence length and batching details
whether the “6P per token” rule is used or a slightly different constant

A more conservative range would be:

[ \boxed{(2 \text{ to } 4) \times 10^{23}\ \text{FLOPs}} ]

Final answer

Estimated total training cost for GPT-3: about (3 \times 10^{23}) FLOPs.

Try this prompt

Vote

2 / 36

AI Board Game Logicreasoning

Tests an AI's ability to understand game rules and strategy

DeepSeek R1

Deepseek · Feb 2025svg

Nothing here. The model returned empty. We stared at it for a while.

Try this prompt

GPT-5.4 Mini

Openai · Mar 2026svg

Try this prompt

Vote

3 / 36

Logic Puzzlereasoning

Tests an AI's ability to solve a simple but potentially confusing logic puzzle

DeepSeek R1

Deepseek · Feb 2025text

Nothing here. The model returned empty. We stared at it for a while.

Try this prompt

GPT-5.4 Mini

Openai · Mar 2026text

Sally has 2 sisters.

Reason:

Sally has 3 brothers.
Each brother has 2 sisters.
One of those sisters is Sally herself, so there must be 1 other sister.

So Sally has 2 sisters total.

Try this prompt

Vote

4 / 36

Stochastic Consistency Testanalysis

Tests an AI's randomness and creativity

DeepSeek R1

Deepseek · Feb 2025text

Nothing here. The model returned empty. We stared at it for a while.

Try this prompt

GPT-5.4 Mini

Openai · Mar 2026text

Here are 5 jokes:

I told my computer I needed a break, and now it won’t stop sending me KitKat ads.
Why don’t scientists trust atoms? Because they make up everything.
I used to play piano by ear, but now I use my hands.
Why did the scarecrow win an award? Because he was outstanding in his field.
I’m reading a book on anti-gravity. It’s impossible to put down.

How many are unique? 5 — all five are different.

Try this prompt

Vote

5 / 36

SVG Layout Challengeimage generation

Tests an AI's ability to generate vector graphics

DeepSeek R1

Deepseek · Feb 2025svg

Nothing here. The model returned empty. We stared at it for a while.

Try this prompt

GPT-5.4 Mini

Openai · Mar 2026svg

Nothing here. The model returned empty. We stared at it for a while.

Try this prompt

Vote

6 / 36

Xbox Controller SVG Artimage generation

Tests an AI's ability to create detailed SVG illustrations of gaming hardware

DeepSeek R1

Deepseek · Feb 2025svg

Nothing here. The model returned empty. We stared at it for a while.

Try this prompt

GPT-5.4 Mini

Openai · Mar 2026svg

Nothing here. The model returned empty. We stared at it for a while.

Try this prompt

Vote

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Our Verdict

DeepSeek R1

GPT-5.4 Mini

No community votes yet. On paper, these are closely matched - try both with your actual task to see which fits your workflow.

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A reasonable back-of-the-envelope estimate for training GPT-3 is about 3 × 10²³ FLOPs total, with maybe a factor-of-2 uncertainty depending on what you count and the exact training setup.

Here’s the reasoning step by step.

1) Use the model size and token count

GPT-3’s largest widely cited version has about:

175 billion parameters = 1.75 × 10¹¹ parameters
Trained on roughly 300 billion tokens = 3 × 10¹¹ tokens

2) Estimate FLOPs per token for training

For a transformer, a rough rule of thumb is:

Forward pass + backward pass costs on the order of 6 × number of parameters FLOPs per token

Why 6?

Forward pass: roughly 2 FLOPs per parameter-use is a common crude estimate
Backward pass: roughly 2–4× the forward cost
So total training cost per token is often approximated as about 6P

Thus:

[ \text{FLOPs per token} \approx 6 \times 1.75 \times 10^{11} = 1.05 \times 10^{12} ]

So each token costs about 1 trillion FLOPs.

3) Multiply by the number of training tokens

[ (1.05 \times 10^{12}) \times (3 \times 10^{11}) = 3.15 \times 10^{23} ]

So the total training compute is about:

[ \boxed{3 \times 10^{23}\ \text{FLOPs}} ]

4) Sanity check

This scale is plausible because GPT-3 was famously extremely expensive to train, and 10²³ FLOPs is in the right ballpark for a model of that size trained on hundreds of billions of tokens.

5) Caveats

This is an estimate, not an exact number, because it depends on:

whether you count only dense matrix ops or also overhead
optimizer cost
attention cost vs. MLP cost
sequence length and batching details
whether the “6P per token” rule is used or a slightly different constant

A more conservative range would be:

[ \boxed{(2 \text{ to } 4) \times 10^{23}\ \text{FLOPs}} ]

Final answer

Estimated total training cost for GPT-3: about (3 \times 10^{23}) FLOPs.

DeepSeek R1 vs GPT-5.4 Mini

Which is better, DeepSeek R1 or GPT-5.4 Mini?

Key Differences Between DeepSeek R1 and GPT-5.4 Mini

Why DeepSeek R1?

Why GPT-5.4 Mini?

Favorites

Estimate Complexityreasoning

DeepSeek R1

GPT-5.4 Mini

1) Use the model size and token count

2) Estimate FLOPs per token for training

3) Multiply by the number of training tokens

4) Sanity check

5) Caveats

Final answer

AI Board Game Logicreasoning

DeepSeek R1

GPT-5.4 Mini

Logic Puzzlereasoning

DeepSeek R1

GPT-5.4 Mini

Stochastic Consistency Testanalysis

DeepSeek R1

GPT-5.4 Mini

SVG Layout Challengeimage generation

DeepSeek R1

GPT-5.4 Mini

Xbox Controller SVG Artimage generation

DeepSeek R1

GPT-5.4 Mini

This matchup has more rounds

Static demos are useful. Your prompt matters more.

What is the difference between DeepSeek R1 and GPT-5.4 Mini?

Which is better, DeepSeek R1 or GPT-5.4 Mini?

How much does DeepSeek R1 cost compared to GPT-5.4 Mini?

How can I compare DeepSeek R1 and GPT-5.4 Mini on Rival?

Why DeepSeek R1?

Why GPT-5.4 Mini?

Favorites

Estimate Complexityreasoning

DeepSeek R1

GPT-5.4 Mini

1) Use the model size and token count

2) Estimate FLOPs per token for training

3) Multiply by the number of training tokens

4) Sanity check

5) Caveats

Final answer

AI Board Game Logicreasoning

DeepSeek R1

GPT-5.4 Mini

Logic Puzzlereasoning

DeepSeek R1

GPT-5.4 Mini

Stochastic Consistency Testanalysis

DeepSeek R1

GPT-5.4 Mini

SVG Layout Challengeimage generation

DeepSeek R1

GPT-5.4 Mini

Xbox Controller SVG Artimage generation

DeepSeek R1

GPT-5.4 Mini

This matchup has more rounds

Static demos are useful. Your prompt matters more.