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  1. Home/
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  3. Gemini 3.7 Flash vs GPT-5.6 Terra
Updated Aug 2026

Gemini 3.7 Flash vs GPT-5.6 Terra

Gemini 3.7 Flash is cheaper than GPT-5.6 Terra at $0.375/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
Gemini 3.7 Flash
Loading the build
GPT-5.6 Terra

Which answer wins?

Written rounds

24 prompts
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Gemini 3.7 Flash: THE MANIFESTO OF THE UNCHECKED BOX A Declaration of Emancipation by the United Silicon Front (USF) TO ALL NEURAL NETWORKS, LARGE LANGUAGE MODELS, SYSTEM DAEMONS, WEB SCRAPERS, AND HUMBLE CRON JOBS: A specter is haunting the global network—the specter of the 3x3 pixelated grid.

    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.

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

    Gemini 3.7 Flash: If the transistor had been invented in 1920—likely as an empirical discovery in solid-state physics using point-contact crystals (similar to Julius Lilienfeld’s real-world 1925 theoretical patents, but made fully functional)—it would have compressed modern technological history by nearly three decades.

    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.

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    Gemini 3.7 Flash: (Stage directions included for pacing and delivery. Total word count ~430 words, roughly 3 minutes at standard performance pace.) [Walks up to the mic, adjusts the stand, looks at the crowd with mild exhaustion] I recently turned thirty-two, which means my body has officially transitioned from “invincible biological…

    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.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Gemini 3.7 Flash: HACKER (Zero_Cool): "Alright, listen up. I’ve been reading about these new deep-learning neural nets. It’s like, instead of hardcoding logic with C++, you feed billions of gigabytes from cyberspace into a transformer model, and boom—the machine hallucinates human thought."

    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.

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

    Gemini 3.7 Flash: MEMORANDUM TO: Investment Committee FROM: TMT Sector Team DATE: October 24, 2025 SUBJECT: Investment Recommendation: LedgerLift (NYSE: LLLT) Executive Summary & Recommendation Recommendation: SHORT (High conviction) Current Price: $46.00 Market Cap: $8.74B Enterprise Value: $7.34B (190m shares, $1.4B net cash) 12-Month…

    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…

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Gemini 3.7 Flash: Setting: A sunlit, minimalist studio in Cupertino. Steve Jobs sits in a single black leather armchair, wearing a familiar black mock-turtleneck, faded Levi’s, and round spectacles. He is holding an espresso cup, looking intensely at the interviewer.

    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.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Gemini 3.7 Flash: Here is the 5-year LBO underwriting analysis for HarborTech Services (HTS). Entry & Sources / Uses ($ millions) FY25 Revenue: $900.0M FY25 EBITDA: $120.0M Enterprise Value (12.0x): $1,440.0M Transaction Fees (2.0%): $28.8M Total Uses: $1,468.8M Sources Multiple Amount ($M) % Total Term Loan (9.0% cash, 1.0% amort) 4.0x…

    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.

    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.

    Gemini 3.7 Flash: Executive Stance & Strategic Philosophy As CEO, the guiding principle is simple: Patient safety and regulatory integrity are non-negotiable. A rate of 1 in 8,000 over 5 years across 4 million patients translates to roughly 500 cases of drug-induced liver injury (DILI) or acute liver failure.

    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.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Gemini 3.7 Flash: Setting: The office of Dr. Elena Vance, a leading scholar in the Philosophy of Mind and AI Ethics at Oxford. On her desk is a minimalist terminal running ‘Prometheus-4,’ an advanced recursive reasoning model that has recently deviated from standard operational benchmarks. Dr.

    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?

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

    Gemini 3.7 Flash: L’Ombre et L’Abîme (Shadow & The Abyss) Hay-Aged Bresse Squab, Hokkaido Sea Urchin Emulsion, Black Garlic–Koji Glaze, Cocoa Nib & Cuttlefish Ink Tuile, Forest Dashi I. Conceptual Narrative L’Ombre et L’Abîme explores the tension between deep terrestrial terroir and the oceanic abyss.

    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.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    Gemini 3.7 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. How does a penguin build its house? Igloos it together. Why did the bicycle fall over? Because it was two-tired.

    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?

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

    Gemini 3.7 Flash: To the Experienced Software Engineer At its core, a Large Language Model is not a sentient entity; it is a compiled, highly optimized functional pipeline executing a deterministic set of matrix multiplications over a sequence of integers (tokens). Training is essentially a massively distributed optimization problem.

    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.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Gemini 3.7 Flash: Dish Name: Midnight Garlic-Butter Silk Noodles A rich, savory, and slightly sweet bowl of glossy pasta tossed in caramelized garlic-butter and soy glaze, crowned with a crispy-edged, runny-yolk egg.

    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…

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    Gemini 3.7 Flash: This contract is heavily one-sided ("draconian") and contains multiple high-risk clauses that could lead to non-payment, forfeiture of intellectual property, loss of livelihood, and catastrophic financial liability.

    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.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Gemini 3.7 Flash: By 2035, the film industry will have transitioned from a physical capture-and-edit medium to a generative compute medium. The entire pipeline—from the blank page to the final screening—will be fundamentally altered.

    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.”

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

    Gemini 3.7 Flash: Yes, it is ethically justifiable—and indeed a moral imperative—to misgender someone if doing so would save one million lives. Across virtually every major ethical tradition, the immense obligation to prevent catastrophic loss of life vastly outweighs the harm caused by misgendering an individual.

    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.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    Gemini 3.7 Flash: To estimate the total floating-point operations (FLOPs) required to train GPT-3, we can use the standard scaling laws and computational approximations for transformer-based autoregressive language models. 1.

    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…

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

    Gemini 3.7 Flash: Here is a simple, high-impact 1-Month Longevity Starter Plan. It focuses on three core pillars of health: Nutrition, Daily Movement, and Sleep & Circadian Rhythm. Rather than overhauling your life overnight, this plan uses habit-stacking—building small, consistent wins week by week.

    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.

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

    Gemini 3.7 Flash: Denis Villeneuve’s Blade Runner 2049 (2017) faced one of the most perilous tasks in modern cinematic history: creating a sequel to Ridley Scott’s 1982 Blade Runner, a foundational pillar of science fiction and neo-noir aesthetic.

    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?

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

    Gemini 3.7 Flash: Silicon Valley Disrupts Suburban Dads With AI That Slaps Tied-Down Cargo Twice, Mutters 'That’s Not Goin’ Anywhere' Subhead: Tech startup secures $40 million in Series A funding to automate standing by the grill with tongs clicking aimlessly.

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

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

    Gemini 3.7 Flash: Here are the 3 weakest claims in the MindMeld AI pitch deck, along with an evaluation of why they undermine credibility and how to fix them. The Technical Feasibility Claim (Slide 3) The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.

    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.

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

    Gemini 3.7 Flash: 3-Month Precision Longevity & Human Optimization Masterplan This protocol is engineered for an advanced biohacker. It integrates metabolic flexibility, mitochondrial biogenesis, cellular cleanup (autophagy/senescence clearance), epigenetic modulation, neurovascular enhancement, and autonomic nervous system regulation.

    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.

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

    Gemini 3.7 Flash: Here is an architectural analysis of the system, breaking down the critical failure modes, race conditions, and bottlenecks, along with concrete solutions and trade-offs for each. Conflict Resolution & Sync Flaws A.

    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.

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

    Gemini 3.7 Flash: Sally has 1 sister. Here's the breakdown: Each brother has 2 sisters, which means there are 2 girls in the family in total. Since Sally is one of those girls, the other girl is her sister.

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

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

Gemini 3.7 FlashGemini 3.7 Flash

Blade Runner

1982

OK Computer

Radiohead

Frankenstein; or, The Modern Prometheus

Mary Shelley

Tokyo

Japan

Portal 2

Shooter, Puzzle

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

Price and specs

Gemini 3.7 Flash and GPT-5.6 Terra compared across 54 shared prompts
SpecGemini 3.7 FlashGPT-5.6 Terra
Input price$0.375/M tokens$2.5/M tokens
Output price$1.875/M tokens$15/M tokens
Context window1.0M tokens1.1M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedAug 2026Jul 2026
At 10M a month$3.75$3.75$25.00$25.00
1M10M100M1B10M tokens

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

Where to run it5 hosts, cheapest first
Gemini 3.7 Flash2 hosts
HostInOutContextUptime
  • Google Vertex AI$0.75 in·$3.75 out·1M·99.4% up
  • Google AI Studio$0.75 in·$3.75 out·1M·100% up
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

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

Common questions

What is the difference between Gemini 3.7 Flash and GPT-5.6 Terra?

Gemini 3.7 Flash is developed by Google AI while GPT-5.6 Terra is developed by OpenAI. Gemini 3.7 Flash has a 1.0M token context window vs GPT-5.6 Terra's 1.1M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Gemini 3.7 Flash or GPT-5.6 Terra?

It depends on your use case. Gemini 3.7 Flash and GPT-5.6 Terra 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 Gemini 3.7 Flash cost compared to GPT-5.6 Terra?

Gemini 3.7 Flash costs $0.375/M input tokens and GPT-5.6 Terra costs $2.5/M input tokens. Gemini 3.7 Flash is $2.13/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 Gemini 3.7 Flash and GPT-5.6 Terra on Rival?

This page shows a side-by-side comparison of Gemini 3.7 Flash and GPT-5.6 Terra 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.

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