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  1. Home/
  2. Compare/
  3. GPT-5.6 Terra vs Mistral Nemo
Updated Jul 2026

GPT-5.6 Terra vs Mistral Nemo

Mistral Nemo is cheaper than GPT-5.6 Terra at $0.03/M vs $2.5/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
GPT-5.6 Terra
Loading the build
Mistral Nemo

Which answer wins?

Written rounds

24 prompts
  • 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.

    Every model's answer to this prompt
  • 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?

    Every model's answer to this prompt
  • 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).

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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…

    Every model's answer to this prompt
  • 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…

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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…

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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?

    Every model's answer to this prompt
  • 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…

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.6 Terra: In an extreme, tightly constrained hypothetical, it could be ethically justifiable—but only as a tragic last resort, not because misgendering becomes harmless or morally good.

    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…

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-5.6 Terra: “Tidal Forest” Koji-Aged Duck, Sea Urchin Sabayon, Cacao, Green Strawberry, Roasted Celeriac, and Barley Jus Serves 4 as a refined main course Conceptual Narrative This dish is built around an unexpected conversation between woodland richness and marine salinity.

    Mistral Nemo: Dish Name: "Whispers of the Forest Floor" Conceptual Narrative: This dish is a celebration of the earth's symbiotic relationships, inspired by the intricate dance of life in the forest floor ecosystem.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-5.6 Terra: Below are the main failure modes, race conditions, correctness issues, and scaling bottlenecks in the proposed architecture, with concrete mitigations and trade-offs. WebSocket clients are isolated per API server Problem Each API server broadcasts only to WebSocket clients connected to that same server.

    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.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GPT-5.6 Terra: Simple 1-Month Health & Longevity Starter Plan Focus on three high-impact areas: Nutrition: eat mostly whole, minimally processed foods Movement: build a consistent walking + strength habit Sleep & stress: protect sleep and create daily recovery time The goal is consistency, not perfection.

    Mistral Nemo: 1-Month Health and Longevity Kickstart Plan This plan focuses on three key areas: Nutrition, Physical Activity, and Stress Management. Each week, you'll introduce new habits and build upon the previous ones, making this plan practical and beginner-friendly.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-5.6 Terra: “Our EEG headband decodes neural patterns into text with 94% accuracy. Works with any language, any device.” Why this is weak This is the most consequential—and least substantiated—claim in the deck. Non-invasive EEG has major signal-quality limits.

    Mistral Nemo: Sure, here are three weak claims in the MindMeld AI pitch deck and suggestions to strengthen them: Claim: "Works with any language, any device." Weakness: This claim is broad and lacks specific evidence. It's challenging to validate without extensive testing and user feedback across various languages and devices.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    GPT-5.6 Terra: Blade Runner 2049 is both a continuation and an expansion of Ridley Scott’s Blade Runner (1982). Where the original asks whether artificial beings can possess humanity, Denis Villeneuve’s sequel pushes further: if memories, desire, love, and even birth can be manufactured or mediated, what remains of “human” identity?

    Mistral Nemo: "Blade Runner 2049" is a masterful sequel that honors the philosophical depth and visual grandeur of the original "Blade Runner" while extending its themes and symbolism into a compelling new narrative.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-5.6 Terra: The answer depends heavily on what “invented in 1920” means. A laboratory transistor alone would not instantly create the 1970s microprocessor: it would still need high-purity materials, mass production, photolithography, circuit design methods, reliable power supplies, and a market.

    Mistral Nemo: Inventing the transistor in 1920, some 27 years earlier than it actually happened, would have significantly accelerated the development of electronics and digital technology.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-5.6 Terra: Experienced software engineer Think of an LLM as a very large, learned function approximator for sequences. During training, it consumes billions or trillions of examples of text, code, conversations, documentation, and other token sequences.

    Mistral Nemo: 1. For the experienced software engineer: Large language models like GPT or Claude learn and generate text through a process that might seem simple at first, but is remarkably effective.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-5.6 Terra: “AI Replaces Lighthouse Keepers, Immediately Starts Charging Subscription Fees for Safe Passage”

    Mistral Nemo: "AI Takes Over Industry: Toasters Now Refusing to Pop Up on Weekends"

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.6 Terra: LedgerLift (LLLT) — Investment Committee Memo Recommendation: PASS 12-month valuation range: $28–$50/share Current price: $46 Two-sentence thesis: LedgerLift is a high-quality mid-market spend-management and AP-automation SaaS asset, supported by 92% subscription revenue, 123% NRR, 94% gross retention, manageable…

    Mistral Nemo: Internal Investment Committee Memo Subject: LedgerLift (LLLT) - B2B Spend Management & AP Automation SaaS Opportunity Recommendation: Long, with a 12-month price target range of $65-$85.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.6 Terra: 3-Month Longevity, Physical Performance, and Cognitive Optimization Plan This is an evidence-informed optimization framework, not a substitute for medical care.

    Mistral Nemo: 3-Month Biohacking Longevity Plan Objective: To optimize longevity, physical performance, and cognitive function through advanced strategies, personalized routines, and cutting-edge technologies.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GPT-5.6 Terra: Sally has 1 sister. The 2 sisters each brother has are Sally and her sister.

    Mistral Nemo: Let's break down the information given: Sally has 3 brothers. Each of Sally's brothers has 2 sisters. Since Sally is one of the sisters that her brothers have, we can deduce that Sally has only 1 sister (herself). Final answer: Sally has 1 sister.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

GPT-5.6 TerraGPT-5.6 Terra

Spirited Away

2001

Blue

Jonas Blue

The Left Hand of Darkness

Ursula K. Le Guin

Kyoto

Japan

Outer Wilds

Indie, Adventure

Mistral NemoMistral Nemo

The Shawshank Redemption

1994

Sgt Peppers Lonely Hearts Club Band

The Beatles

To Kill a Mockingbird

Harper Lee

Paris

France

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

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.

GPT-5.6 Terra and Mistral Nemo compared across 54 shared prompts
SpecGPT-5.6 TerraMistral Nemo
Input price$2.5/M tokens$0.03/M tokens
Output price$15/M tokens$0.07/M tokens
Context window1.1M tokens128K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Jul 2024
At 10M a month$25.00$25.00$0.30$0.30
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it8 hosts, cheapest first
GPT-5.6 Terra3 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$12.00 out·1.1M·100% up
  • OpenAI$2.00 in·$12.00 out·1.1M·100% up
  • Amazon Bedrock$2.20 in·$13.20 out·1.1M–not listed
Mistral Nemo5 hosts
HostInOutContextUptime
  • DDekaLLMfp8$0.02 in·$0.03 out·131k·100% up
  • Iio.netfp16$0.02 in·$0.02 out·128k·100% up
  • DDeepInfrafp8$0.03 in·$0.03 out·131k·100% up
  • PParasailfp8$0.03 in·$0.03 out·131k·99.9% up
  • Mistral$0.15 in·$0.15 out·131k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GPT-5.6 Terra and Mistral Nemo?

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.

Which is better, GPT-5.6 Terra or Mistral Nemo?

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.

How much does GPT-5.6 Terra cost compared to Mistral Nemo?

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.

How can I compare GPT-5.6 Terra and Mistral Nemo on Rival?

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.

More comparisons

Against the newest arrivals

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  • GPT-5.6 Terra vs GPT-6.1 SolLanded Sep 2026
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  • GPT-5.6 Terra vs Solar Mini 4Landed Sep 2026
  • Mistral Nemo vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

  • GPT-5.6 Terra vs GPT-5.6 LunaVersion compare
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  • Mistral Nemo vs Mistral Small 4Same lab
  • Mistral Nemo vs Ox AlphaSame size
  • Mistral Nemo vs Qwen3.5 122B A10BSame size
  • Mistral Nemo vs Qwen3.5 27BNew provider
  • Mistral Nemo vs Qwen3.5 35B A3BNew provider
  • Mistral Nemo vs Qwen3.5 397B A17BNew provider

Model pages

  • GPT-5.6 Terra58 outputs, specs and price
  • Mistral Nemo58 outputs, specs and price
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