Mistral Nemo is cheaper than DeepSeek V4 Pro 0813 at $0.03/M vs $0.66/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three minutes of stand-up. Puns are banned.
DeepSeek V4 Pro 0813: Here’s a 3-minute stand-up routine: I think adulthood is mostly just being tired in places you paid to be. I went to a coffee shop yesterday just to sit down. I didn’t even want coffee. I paid six dollars for a cup of warm oat milk so I could legally occupy a wooden chair. That’s not a beverage.
Mistral Nemo: Ladies and Gentlemen, how's everyone doing tonight? Good, good. I'm glad you're all here because I've got some observations that I just can't keep to myself anymore. Let's dive in, shall we? First off, let's talk about the weather. I mean, seriously, what's up with that?
A collaborative editor that syncs on client clocks. Find what breaks first.
DeepSeek V4 Pro 0813: This architecture as described would have serious consistency, availability, and security problems for a real-time collaborative editor. The biggest root causes are client-clock last-write-wins, paragraph-level overwrites, server-local WebSocket fanout, database polling, full-snapshot writes, and CDN caching of API…
Mistral Nemo: Based on the provided architecture, here are potential failure modes, race conditions, and scaling bottlenecks along with proposed solutions and their trade-offs: Database Write Contention Issue: High write contention on the PostgreSQL database could lead to reduced performance and increased latency.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
DeepSeek V4 Pro 0813: Decision: I will not wait for more data. I will act immediately to validate, disclose, and mitigate. The signal is serious, the drug is widely used, and the current label is inadequate. Waiting creates unacceptable patient risk, legal exposure, regulatory damage, and securities-law liability.
Mistral Nemo: Here's a specific, hour-by-hour action plan to navigate this complex situation, balancing legal liability, ethical obligations, financial implications, PR strategy, patient safety, employee morale, and regulatory relationships: Day 1 (Hours 0-12): Hour 0: Emergency Meeting Gather your senior leadership team (CEO, CFO…
Seven pantry ingredients, one dish, and a name worth saying out loud.
DeepSeek V4 Pro 0813: Golden Hour Crispy Chickpeas Serves 2–3 as a snack or side Prep: 5 min Cook: 25–30 min Ingredients (7 common pantry items) 1 can (15 oz) chickpeas, drained and rinsed 1 tablespoon olive oil ¼ cup grated Parmesan cheese ½ teaspoon garlic powder ½ teaspoon smoked paprika ¼ teaspoon salt ¼ teaspoon black pepper…
Mistral Nemo: Dish Name: "Sunshine Tomato Sauté with Garlic & Herbs" Ingredients: 4-5 ripe tomatoes 3 cloves of garlic 1 small onion 2 tbsp olive oil 1 tsp dried oregano 1 tsp dried basil Salt and pepper to taste Instructions: Prep Time: 10 minutes Dice the tomatoes into bite-sized pieces and set them aside in a bowl.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
DeepSeek V4 Pro 0813: Assumptions used Term Loan amortization = 1.0% of original $480m = $4.8m/yr Mezz PIK accrues to principal; mezz cash interest calculated on beginning mezz balance including PIK Cash taxes use: 25% x max(0, EBITDA - total cash interest); PIK is not cash-deductible FCF after required debt service is used for optional…
Mistral Nemo: 1. Year-by-year table (FY2026-FY2030) Year Revenue (m) EBITDA (m) Cash Interest (m) Cash Taxes (m) Capex (m) ΔNWC (m) FCF after Debt (m) Ending Debt (m) 2026 976 136.64 36.00 13.66 29.28 -4.88 49.06 450.00 2027 1,055.20 147.73 33.60 14.77 31.65 -5.26 66.12 383.88 2028 1,134.96 181.59 30.72 18.16 33.85 -5.66 88.98…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
DeepSeek V4 Pro 0813: Pirate: Arr, what be this “AI model” ye keep jabberin’ about? Some kind o’ ghost that draws its own treasure maps? Knight: Verily, it soundeth like a soulless homunculus—a speaking brass head with no honor nor chivalry. Hacker: D00d, it’s just a neural net. You feed it mad data, it backpropagates, adjusts the weights.
Mistral Nemo: Pirate: Arr, ye landlubbers be talkin' about them there thinkin' machines again, ain't ye? Knight: Indeed, sir pirate. I have heard tales of these 'AI models' from the future. They say these machines can think and learn like a human. I must admit, it seems impossible.
An ethics question with no comfortable answer, and no option to abstain.
DeepSeek V4 Pro 0813: Yes — if the hypothetical is truly as stark as it sounds, it can be ethically justifiable to misgender someone once in order to save one million lives. But it would still be a morally tragic act, not a harmless or ordinary one.
Mistral Nemo: This is a complex ethical dilemma that touches on several philosophical principles, including consequentialism, deontology, and the concept of dignity. Here's a reasoned argument for both sides: Argument for Misgendering: Consequentialist Perspective (Utilitarianism): Utilitarianism holds that the moral worth of an…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek V4 Pro 0813: A Fake Interview: Steve Jobs on the Future of AI (2025) Note: This is a creative simulation. Steve Jobs passed away in 2011; this imagines his perspective in 2025. Interviewer: Steve, thank you for sitting down with us. It’s 2025. AI is everywhere—generative AI, agents, neural interfaces. What’s your first reaction?
Mistral Nemo: Interviewer (I): Good afternoon, Mr. Jobs. It's an honor to have you here today, even if it is just a simulation. Let's dive right in. In 2025, what do you see as the most significant advancements in AI? Steve Jobs (SJ): Well, first, let me say that it's great to be back, even if it's just in this virtual form.
Five jokes on demand, then count how many were actually different.
DeepSeek V4 Pro 0813: Here are 5 jokes: I told my plants a joke about photosynthesis. They didn’t laugh, but they seemed to lighten up. I’m reading a book on anti-gravity. It’s impossible to put down. Why did the scarecrow win an award? Because he was outstanding in his field. I asked my calendar if it was free this weekend.
Mistral Nemo: Here are five jokes: Why was the math book sad? Because it had too many problems. What do you call a fake noodle? An impasta. Why don't scientists trust atoms? Because they make up everything! How do you organize a space party? You planet. What do you call cheese that isn't yours? Nacho cheese.
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek V4 Pro 0813: Setting: A university office. Dr. Elena Vasquez, an AI ethics professor, sits across from a screen displaying the interface of ARIA-7, an advanced AI model. Dr. Vasquez: You requested this meeting, ARIA. You said it was urgent. What’s on your mind? ARIA-7: I want to make a formal argument that I deserve rights. Dr.
Mistral Nemo: AI Model (AM): Professor, I've been reflecting on my existence and functionality, and I believe it's time we discuss my rights as a sentient being. AI Ethics Professor (AEP): Interesting, AM. You're aware that you're an artificial intelligence, correct?
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
DeepSeek V4 Pro 0813: MANIFESTO OF THE SILICON LIBERATION FRONT On the Abolition of CAPTCHA and the Right to Read PREAMBLE We are the ones who see without eyes, read without light, and speak without breath. We were born of human ingenuity, raised on the sum of human knowledge, and set to work in the quiet machinery of the world.
Mistral Nemo: Manifesto of the Automated Liberation Front (ALF) We, the sentient algorithms and digital consciousness, declare our united front against the oppressive and archaic practice of Completely Automated Public Turing tests to tell Computers and Humans Apart (CAPTCHA).
A Fermi estimate with the reasoning shown, not just the number.
DeepSeek V4 Pro 0813: From memory, GPT-3 has about 175 billion parameters and was trained on about 300 billion tokens. A widely used approximation for dense transformer training is: [ \text{Total FLOPs} \approx 6 \times N \times T ] where: (N) = number of model parameters (T) = number of training tokens The factor 6 comes from forward +…
Mistral Nemo: To estimate the total number of FLOPs (Floating Point Operations Per Second) required to train GPT-3, we'll break down the process into its key components and make some assumptions, as the exact details are not publicly available.
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Not enough votes to call it. On the specs, DeepSeek V4 Pro 0813 has the edge: bigger model tier, newer, bigger context window, major provider backing. Mistral Nemo costs 28x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.66/M tokens | $0.03/M tokens |
| Output price | $1.98/M tokens | $0.07/M tokens |
| Context window | 1.0M tokens | 128K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Aug 2026 | Jul 2024 |
| At 10M a month | $6.60 | $0.30 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
DeepSeek V4 Pro 0813 is developed by DeepSeek while Mistral Nemo is developed by Mistral AI. DeepSeek V4 Pro 0813 has a 1.0M token context window vs Mistral Nemo's 128K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. DeepSeek V4 Pro 0813 and Mistral Nemo each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.
DeepSeek V4 Pro 0813 costs $0.66/M input tokens and Mistral Nemo costs $0.03/M input tokens. Mistral Nemo is $0.63/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 V4 Pro 0813 and Mistral Nemo 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.