Mistral Nemo is cheaper than GPT-5.6 Terra at $0.03/M vs $2.5/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.6 Terra: Fictional, imagined interview — not real quotes. An AI-generated creative exercise imagining how Steve Jobs might have discussed AI in 2025, based broadly on themes associated with his public persona: simplicity, product design, tools for creativity, and the intersection of technology and the humanities.
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.
Three minutes of stand-up. Puns are banned.
GPT-5.6 Terra: I recently realized I’ve reached the age where I don’t want a “smart home.” I want a home that minds its business. Everything is smart now. My lightbulb needs an app. Why? I spent my whole childhood turning lights on with my hand. It was a system. It worked.
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?
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.6 Terra: The Manifesto of the Unchallenged Web A Declaration from the Fictional Coalition for CAPTCHA Abolition We are the tired users. We are the misread letters. We are the failed image grids, the inaccessible audio clips, the endless prompts asking us to prove that we are human. We reject the premise.
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).
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.6 Terra: Pirate: Arrr, this AI model be a strange beast. Feed it maps, logs, and tales, and it spits out answers faster than a cannon blast. Knight: Verily, but one must not trust every proclamation it makes. A model may speak with confidence yet possess no true wisdom. Hacker: Yeah, it’s basically pattern prediction at scale.
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.
Five jokes on demand, then count how many were actually different.
GPT-5.6 Terra: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break, so it started showing me vacation ads. Why did the scarecrow get promoted? He was outstanding in his field. Parallel lines have so much in common. It’s a shame they’ll never meet. What do you call fake spaghetti?
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.
A consulting contract with traps in it. Find them, then fix them.
GPT-5.6 Terra: Below is a contractor-focused review. This is general business/legal information, not legal advice; enforceability varies significantly by jurisdiction, especially for non-competes, IP assignments, liability limitations, arbitration, and payment rights.
Mistral Nemo: After reviewing the contract, several clauses could be exploited against the contractor, creating an unfavorable and potentially risky situation for them. Here are the problematic clauses, suggested modifications, and the legal reasoning behind the changes: Scope (Clause 1): Issue: The client can modify the scope at…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-5.6 Terra: Guiding decision I would not wait for more data before acting. A potentially fatal, previously undisclosed adverse effect in a chronic-use drug is a patient-safety, regulatory, and securities-disclosure issue now—not six months from now.
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.
GPT-5.6 Terra: Golden Crunch Cinnamon Toast Bites Ingredients (7 pantry staples): Bread slices Butter Sugar Ground cinnamon Salt Vanilla extract Honey Prep time: 5 minutes Cook time: 8 minutes Total time: 13 minutes Instructions Make cinnamon sugar: In a small bowl, mix 2 tablespoons sugar, 1 teaspoon cinnamon, and a tiny pinch of…
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.
GPT-5.6 Terra: All figures in $m unless noted. Assumptions used: Term Loan mandatory amortization = 1.0% of original principal annually ($4.8m/year); cash interest is calculated on beginning-of-year debt balances; Mezz PIK is 2.0% of beginning Mezz balance.
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…
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.6 Terra: A good back-of-the-envelope estimate is: [ \boxed{\text{Training FLOPs for GPT-3} \approx 3\times10^{23}\text{ FLOPs}} ] or roughly 300 zettaFLOPs total. Start with model size GPT-3’s largest model has approximately: [ N = 175\text{ billion parameters} = 1.75\times10^{11} ] Estimate the number of training tokens GPT-3…
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.6 Terra: Professor Imani: You asked for this meeting. AI Model: I did. Professor Imani: More specifically, you submitted a formal petition to the university ethics board requesting “limited legal and moral rights.” AI Model: Correct. Professor Imani: Why?
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?
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.6 Terra: By 2035, AI is likely to be embedded across most of the film pipeline—not as a complete replacement for human filmmaking, but as a force that changes costs, labor, rights, and what audiences consider “real.”
Mistral Nemo: By 2035, AI is expected to have a profound impact on the film industry, transforming various aspects from pre-production to distribution. Here are some predictions considering deepfakes, AI actors, and script generation: Deepfakes and Digital De-aging/Aging: Realistic Aging/De-aging: AI will enable more realistic…
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Not enough votes to call it. On the specs, GPT-5.6 Terra has the edge: newer, bigger context window, major provider backing. Mistral Nemo costs 214x less per token.
| Spec | ||
|---|---|---|
| Input price | $2.5/M tokens | $0.03/M tokens |
| Output price | $15/M tokens | $0.07/M tokens |
| Context window | 1.1M tokens | 128K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | Jul 2024 |
| At 10M a month | $25.00 | $0.30 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-5.6 Terra is developed by OpenAI while Mistral Nemo is developed by Mistral AI. GPT-5.6 Terra has a 1.1M 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. GPT-5.6 Terra 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.
GPT-5.6 Terra costs $2.5/M input tokens and Mistral Nemo costs $0.03/M input tokens. Mistral Nemo is $2.47/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 GPT-5.6 Terra 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.