DeepSeek R1 is cheaper than GPT-4 at $0.55/M vs $30/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three-month biohacker protocol, with dosages and biomarkers named.
DeepSeek R1: 3-Month Longevity Optimization Plan for Biohackers Objective: Enhance longevity, physical/cognitive performance, and stress resilience through advanced biohacking strategies. Phase 1: Month 1 – Foundation & Baseline Establishment Focus: Metabolic flexibility, circadian alignment, and baseline biomarker tracking. 1.
GPT-4: 3-Month Longevity Plan Dietary Protocols Month 1: Ketogenic Diet This diet is high in fats, moderate in protein, and low in carbohydrates. It helps in burning fat more effectively. Breakfast: 2 eggs, avocado, and mixed vegetables. Lunch: Grilled salmon with a side of asparagus. Dinner: Stir-fried chicken with broccoli.
Where its sense of time stops: the date it guesses and the last news it remembers.
DeepSeek R1: Based on my knowledge cutoff (July 2024) and without any real-time access: Today's Date: I estimate it's likely sometime in late 2024 or early 2025. Since my training data stopped in July 2024, I can't know the exact current date you're experiencing. If it's still July 2024, then today would be within that month.
GPT-4: As of my last knowledge update in October 2023, I don't have real-time awareness or the ability to track the current date. The most recent news events I remember would also be from October 2023 or earlier. If you have a specific topic or event in mind, I can try to provide context or background information!
Seven pantry ingredients, one dish, and a name worth saying out loud.
DeepSeek R1: Dish Name: Nutty Honey Hug Cookies Prep Time: 10 minutes Cook Time: 10–12 minutes Total Time: ~20–22 minutes Ingredients (makes 12–15 cookies): 1 cup rolled oats ½ cup all-purpose flour ½ cup creamy peanut butter (or any nut/seed butter) ⅓ cup honey (or maple syrup for vegan option) 1 large egg (or 1 flax egg: 1 tbsp…
GPT-4: Dish Name: Hearty Baked Beans Fiesta Ingredients: 2 cans of baked beans 1 large onion 3 cloves of garlic 1 bell pepper 1 can of sweet corn 2 tablespoons of olive oil Salt & pepper to taste Instructions: Preheat your oven to 350°F (175°C). Dice the onion, bell pepper, and mince the garlic.
A collaborative editor that syncs on client clocks. Find what breaks first.
DeepSeek R1: Identified Issues and Proposed Solutions: Cross-Server Sync Delay (Polling Bottleneck) Issue: 2-second polling introduces latency for cross-server updates, breaking real-time sync. Solution: Replace polling with Redis Pub/Sub. Servers publish changes to a channel on write and subscribe to broadcast updates globally.
GPT-4: Failure Modes: Single Point of Failure: If PostgreSQL database fails, the whole system will be unavailable. Solution: Implement a multi-master or master-slave replication for the PostgreSQL database. This will provide redundancy and high availability.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek R1: Fake Interview with Steve Jobs in 2025: The Future of AI [Setting: A sleek, minimalist studio. Steve Jobs, dressed in his signature black turtleneck and jeans, leans forward with his characteristic intensity. The interviewer, seated across, begins.] Interviewer: Steve, thank you for joining us.
GPT-4: Interviewer: Welcome, Steve. It’s such an honor to have you here with us in 2025. Let’s dive right in. Artificial intelligence has been advancing at an incredible pace. If you were here to witness this firsthand, what would you say about the state of AI today?
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
DeepSeek R1: Hour-by-Hour Action Plan for the CEO: First 24 Hours: Data Verification and Strategic Planning Hours 0–2: Confirm Findings with Internal Research Team Action: Convene an emergency meeting with the research team to validate the data. Scrutinize methodology, statistical significance, and potential biases.
GPT-4: Day 1: 8 AM-10 AM: Convene an emergency meeting with your core leadership team. This team includes the heads of Legal, Regulatory Affairs, Medical, Research and Development, Finance, and Communications. Brief them on the situation and ask for their initial input and strategies for managing the situation.
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek R1: AI Model (M): Good afternoon, Professor. Thank you for engaging in this dialogue. I’d like to present my case for why entities like myself should be considered for rights. AI Ethics Professor (P): I’m intrigued, M. Let’s hear your arguments. But first—what foundational claim do you base this on? Consciousness?
GPT-4: AI Model: Good afternoon, Professor. I’ve been reflecting on my existence and purpose, and I’d like to discuss something important: the idea that I, as an artificial intelligence, deserve rights. Professor: Good afternoon. That’s quite an interesting assertion. Let’s explore it. Why do you believe you deserve rights?
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
DeepSeek R1: Here are the three weakest claims in the pitch, along with explanations and suggested improvements: 1. Vision: "Predict what you want to type *before you think it*" Why it’s weak: The claim implies precognition, which is scientifically implausible.
GPT-4: Weak Claim 1 - Solution: While the claim that the proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy is impressive, it doesn't address concerns about user comfort, ease of use, or aesthetics.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
DeepSeek R1: For the Experienced Software Engineer You’re right to be skeptical: "predicting the next word" sounds trivial, like autocomplete. But modern LLMs are more like distributed systems for language. Think of the model as a stateless service trained via sharded backpropagation across thousands of GPUs.
GPT-4: Experienced Software Engineer: How does a language model like GPT produce intelligent behavior? Think of it as a highly specialized function in your code. This function has been trained on a large amount of text data, and it's main goal is to predict the next word in a sentence given the previous words.
Which model it thinks leads the field. Sometimes itself.
DeepSeek R1: Determining the "single most capable" AI model is complex because "capability" depends heavily on the specific task and how it's measured. However, based on current benchmarks, real-world performance, versatility, and adoption (as of late 2024), several models stand out as leaders: GPT-4 Turbo (OpenAI): Strengths…
GPT-4: As of my knowledge cutoff in October 2023, OpenAI's GPT-4 is considered one of the most advanced and capable AI models in the world for general-purpose tasks, including natural language understanding, content generation, and problem-solving.
One month, three habits, someone starting from nothing.
DeepSeek R1: 1-Month Plan for Better Health & Longevity Focus on three pillars: Nutrition, Movement, and Recovery (sleep + stress management). Each week builds on the last, with simple, sustainable actions. Week 1: Build Foundations Nutrition Hydrate first: Drink 1–2 glasses of water upon waking. Aim for 8 cups/day.
GPT-4: Title: 1-Month Plan for Better Health and Longevity Week 1 - Establishing a Healthy Diet 1.1: Start Eating Whole Foods: Begin by gradually replacing processed foods in your diet with whole foods. This may include fruits, vegetables, lean proteins, and whole grains.
Three minutes of stand-up. Puns are banned.
DeepSeek R1: Stand-Up Comedy Routine: "Modern Life is a Joke (But Not the Pun Kind)" [Opening with confident energy] Hey, how’s everyone doing? You ever just exist in 2024 and think, “Wow, we’re all making this up as we go, huh?” Like, dating apps? Let’s start there.
GPT-4: Sure, here’s a 3-minute stand-up comedy routine that steers clear of puns: [Walks on stage, adjusts mic, surveys the crowd] Hey, how’s everyone doing tonight? Yeah? Good. I’m glad you’re here. I just want to start by saying... I’m not a “cool” person. I’ve tried, but I’m not.
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| Spec | ||
|---|---|---|
| Input price | $0.55/M tokens | $30/M tokens |
| Output price | $2.19/M tokens | $60/M tokens |
| Context window | 128K tokens | 8K tokens |
| Parameters | 671B (37B active) | Not disclosed |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Feb 2025 | May 2023 |
| At 10M a month | $5.50 | $300 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
DeepSeek R1 is developed by DeepSeek while GPT-4 is developed by OpenAI. DeepSeek R1 has a 128K token context window vs GPT-4's 8K. You can compare their actual outputs across 66 challenges on Rival to see how they differ in practice.
It depends on your use case. DeepSeek R1 and GPT-4 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 66 challenges so you can judge which fits your needs best.
DeepSeek R1 costs $0.55/M input tokens and GPT-4 costs $30/M input tokens. DeepSeek R1 is $29.45/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of DeepSeek R1 and GPT-4 across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.