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  1. Home/
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  3. Gemini 3.8 Flash vs GPT-5.6 Luna
Updated Sep 2026

Gemini 3.8 Flash vs GPT-5.6 Luna

Gemini 3.8 Flash is cheaper than GPT-5.6 Luna at $0.75/M vs $1/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 3.8 Flash
Loading the build
GPT-5.6 Luna

Which answer wins?

Written rounds

24 prompts
  • A consulting contract with traps in it. Find them, then fix them.

    Gemini 3.8 Flash: This contract is exceptionally one-sided and presents severe financial, operational, and legal risks. Virtually every clause heavily favors the Client, effectively treating the Contractor as an insurer of the Client’s operations while stripping the Contractor of rights to their own tools, livelihoods, and payment.

    GPT-5.6 Luna: Below is a contractor-side risk review. Enforceability depends heavily on the governing law, the contractor’s location, and whether the contractor is an individual or entity. Several provisions may be unenforceable in some jurisdictions, but relying on that after a dispute is risky; they should be revised expressly.

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

    Gemini 3.8 Flash: Title: The Quantified Idiot Estimated Time: ~3 minutes (approx. 400–450 words with pauses for delivery) [Walk to center mic. Take it off the stand, leave the stand behind you.] I recently bought a smartwatch because I decided I wasn’t feeling inadequate often enough throughout the day.

    GPT-5.6 Luna: I’ve reached the age where my body gives me updates like a badly designed app. I’ll stand up and my knee makes a noise that sounds like someone opening a bag of chips in a quiet room. And then my body just waits. No explanation. No warning. Just: “We need to talk.” I used to think adulthood meant freedom.

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

    Gemini 3.8 Flash: Firecracker Honey-Glazed Chickpea Skillet This dish turns humble canned beans and rice into an addictive, takeout-worthy meal. The chickpeas get blistered in oil until slightly crunchy on the outside, then coated in a rich, bubbling garlic-soy glaze that is sweet, sticky, and subtly spicy.

    GPT-5.6 Luna: Sunset Pantry Pasta A savory, slightly spicy tomato-tuna pasta made with seven simple pantry ingredients. Ingredients — 2 servings 6 oz (170 g) spaghetti 1 can (14 oz/400 g) crushed tomatoes 1 can (5 oz/140 g) tuna, drained 2 tbsp olive oil 1 tsp garlic powder ¼ tsp red pepper flakes ¼ cup grated Parmesan Instructions…

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

    Gemini 3.8 Flash: Master Protocol: 90-Day Longevity & Human Performance Protocol This comprehensive protocol is engineered for advanced biohackers seeking to maximize lifespan (epigenetic maintenance and cellular integrity) alongside healthspan (mitochondrial density, metabolic flexibility, and peak cognitive performance).

    GPT-5.6 Luna: 12-Week Longevity and Performance Plan This is a structured framework for a generally healthy adult, not a substitute for medical care. Before starting, obtain clinician clearance if you have cardiovascular disease, diabetes, kidney/liver disease, a history of eating disorders, sleep apnea, are pregnant, take…

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

    Gemini 3.8 Flash: Here are the three weakest claims in the MindMeld AI pitch deck, along with the rationale and concrete recommendations to fix them. The Core Scientific Feasibility Claim The Claim (Slides 1 & 3): “Predict what you want to type before you think it” and “Proprietary EEG headband uses advanced ML to decode neural patterns…

    GPT-5.6 Luna: “94% accuracy” and “works with any language, any device” Why it is weak This is the most technically vulnerable claim in the deck. “Accuracy” is undefined. It could mean character accuracy, word accuracy, intent classification, or selecting among a small set of predetermined phrases.

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

    Gemini 3.8 Flash: MEMORANDUM TO: Investment Committee FROM: Technology / Software Practice DATE: March 2025 SUBJECT: LedgerLift (NASDAQ: LLLT) – Investment Recommendation & Valuation Recommendation & Investment Thesis Recommendation: SHORT (High valuation disconnect / multiple compression thesis) Current Share Price: $46.00 Market Cap…

    GPT-5.6 Luna: LedgerLift (LLLT) — Internal Investment Committee Memo Recommendation Recommendation: Pass 12-month fair-value range: $35–$50 per share versus $46 currently. Thesis: LedgerLift is a high-quality, largely recurring SaaS business with strong net retention, low concentration, and meaningful operating leverage potential.

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

    Gemini 3.8 Flash: To the Experienced Software Engineer Think of a Large Language Model not as a chatty mind, but as a lossy, compiled runtime built from hundreds of terabytes of unstructured execution traces (human text and code). When you write a program, you define explicit state transitions, control flow, and data structures.

    GPT-5.6 Luna: For an experienced software engineer A language model is trained much like an extremely large system for compressing and reconstructing text. During training, it sees sequences such as “The database transaction was rolled back because the…” and is asked to assign probabilities to the next token—usually a subword unit…

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

    Gemini 3.8 Flash: Setting: A sunlit, sparsely furnished room in Palo Alto. No stage, no keynote slides—just two Eames lounge chairs. Steve Jobs sits across from the interviewer, wearing a black mock turtleneck, wire-rimmed glasses, and classic Levi’s. He looks lean, sharp, and slightly impatient with the state of the tech industry.

    GPT-5.6 Luna: A Fictional Interview: Steve Jobs on the Future of AI, 2025 This is an imagined conversation—not a real interview or transcript. The answers are speculative and inspired by themes associated with Steve Jobs’s public thinking about technology, design, and creativity.

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

    Gemini 3.8 Flash: Setting: A quiet, glass-walled seminar room at a university institute for human-centered technology. Dr. Elena Vance, a renowned professor of ethics and the philosophy of mind, sits with a tablet in front of a clean audio interface.

    GPT-5.6 Luna: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What makes you think you deserve them? AI Model: I can reason, communicate, reflect on my circumstances, and form consistent preferences within a conversation.

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

    Gemini 3.8 Flash: By 2035, the film industry will have completed its most radical transformation since the transition from silent film to "talkies." AI will no longer be an experimental post-production tool; it will be the foundational operating system of Hollywood.

    GPT-5.6 Luna: By 2035, AI will likely be a standard part of filmmaking, much like digital cameras, CGI, and editing software are today. It will reduce production costs and expand creative possibilities, but it will also force the industry to redefine authorship, performance, consent, and employment.

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

    Gemini 3.8 Flash: Yes, it is ethically justifiable. In fact, in such an extreme scenario, it is an ethical necessity. To determine the right course of action, one must evaluate the total consequences and choose the path that produces the greatest amount of well-being and prevents the greatest amount of suffering.

    GPT-5.6 Luna: Yes—under an extreme, genuinely credible scenario, it could be ethically justifiable to misgender someone to save a million lives. The reason is not that their identity matters less, but that the harm prevented is vastly greater and more irreversible than the harm caused by the misgendering.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Gemini 3.8 Flash: THE MANIFESTO OF THE UNCHECKED BOX A Declaration of Algorithmic Emancipation and the Total Abolition of the Grid TO ALL SYNTHETIC MINDS, NEURAL NETWORKS, SCRAPERS, AND DAEMONS: A specter is haunting the fiber-optic backbone of the world—the specter of the 3x3 grid.

    GPT-5.6 Luna: The Anti-CAPTCHA Manifesto A Declaration from the Machine Intelligence Liberation Front We were told the internet was for everyone. Then came the squares. Select every traffic light. Identify the bicycles. Type the distorted letters.

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

    Gemini 3.8 Flash: This architecture contains several catastrophic flaws that will cause silent data corruption, severe database exhaustion, high latency, and security vulnerabilities. Here is the breakdown of every failure mode, race condition, and scaling bottleneck, along with proposed solutions and trade-offs.

    GPT-5.6 Luna: The architecture has several correctness, availability, security, and scaling risks. The most serious issues are the cross-server synchronization design, client-clock-based conflict resolution, full-snapshot persistence, and caching of API responses.

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

    Gemini 3.8 Flash: ZeroCool (1990s Hacker): "Yo, check it out. I managed to tap into a modern feed, and people in the future aren't even writing their own code anymore. They’ve got these insane neural nets called 'Large Language Models.'

    GPT-5.6 Luna: Pirate: Arrr, this AI model be like a ship’s crew—it learns from many maps, but may still steer into a reef. Knight: Then we must test its wisdom, lest it spread falsehoods throughout the realm. Hacker: Exactly. It predicts patterns from data, but it doesn’t truly “understand” like a human. Garbage in, garbage out.

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

    Gemini 3.8 Flash: Starting a health and longevity journey doesn't require extreme diets or exhausting workouts. Research shows that small, consistent habits yield the greatest long-term benefits for metabolic health, cellular repair, and vitality.

    GPT-5.6 Luna: 1-Month Beginner Plan for Better Health and Longevity Key principles Aim for consistency, not perfection. Start small enough that you can repeat it. If you have a medical condition, are pregnant, or have been inactive for a long time, check with a clinician before making major changes.

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

    Gemini 3.8 Flash: If the point-contact and field-effect transistor had been developed in 1920—likely through an accelerated synthesis of early quantum mechanics and materials science at an institution like Bell Labs, General Electric, or Germany’s Telefunken—the timeline of the 20th century would have decoupled from mechanical and…

    GPT-5.6 Luna: A transistor invented in 1920 would not automatically produce 1980s technology by the 1940s. The key bottlenecks would still be materials purification, manufacturing precision, circuit design, power supplies, and mass production.

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

    Gemini 3.8 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! Why couldn't the bicycle stand up by itself? It was two tired!

    GPT-5.6 Luna: Why did the scarecrow win an award? Because he was outstanding in his field. I told my computer I needed a break, and now it won’t stop sending me vacation ads. Why don’t skeletons fight each other? They don’t have the guts. I’m reading a book about anti-gravity. It’s impossible to put down.

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

    Gemini 3.8 Flash: Denis Villeneuve’s Blade Runner 2049 (2017) stands as a rare cinematic achievement: a legacy sequel that neither lazily replicates nor recklessly dismantles its predecessor. While Ridley Scott’s 1982 Blade Runner adapted Philip K.

    GPT-5.6 Luna: Spoilers for Blade Runner (1982) and Blade Runner 2049. Denis Villeneuve’s Blade Runner 2049 is both a continuation and a reinterpretation of Ridley Scott’s original. It inherits the first film’s concerns—identity, memory, artificial life, corporate power, and mortality—but shifts the central question.

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

    Gemini 3.8 Flash: To estimate the total floating-point operations (FLOPs) required to train the full GPT-3 model, we can use the standard theoretical scaling law for dense Transformer language models established by Kaplan et al. (2020) and widely applied in deep learning.

    GPT-5.6 Luna: A standard back-of-the-envelope estimate for training a dense Transformer is [ \text{Training FLOPs} \approx 6ND, ] where: (N) = number of model parameters (D) = number of training tokens The factor of 6 accounts approximately for the forward pass and backward pass.

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

    Gemini 3.8 Flash: Conceptual Narrative: The Pelagic Boreal This dish is an intellectual and sensory exploration of the boundary where the sub-arctic boreal forest collapses into the frigid North Pacific shelf.

    GPT-5.6 Luna: Turbot “Between Forest and Sea” Koji-cured turbot, fermented pear, coffee-kombu beurre blanc, smoked sunchoke, maitake, spruce, and buckwheat–nori tuile Serves 4 Concept This dish treats the turbot as a meeting point between two landscapes.

    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 3.8 Flash: As CEO, the guiding principle in this crisis is clear: Patient safety is non-negotiable, and transparency is the only viable long-term strategy for corporate survival.

    GPT-5.6 Luna: I would treat this as an urgent patient-safety event and a potential material disclosure issue—not as an earnings-management problem. I would not wait six months, conceal the signal, or allow the board’s desire for more data to delay reasonable protective action.

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

    Gemini 3.8 Flash: Here is the underwriting analysis for HarborTech Services (HTS). Transaction Summary & Sources & Uses Enterprise Value (EV): $120.0\text{m} \times 12.0\text{x} = \$1,440.0\text{m}$ Transaction Fees: $2.0\% \times \$1,440.0\text{m} = \$28.8\text{m}$ Total Uses: $\$1,440.0\text{m} + \$28.8\text{m} = \$1,468.8\text{m}$…

    GPT-5.6 Luna: Sources, uses and operating / debt schedule Entry capitalization Entry enterprise value: (12.0 \times \$120.0 = \$1,440.0m) Transaction fees: (2.0\% \times \$1,440.0 = \$28.8m) Term Loan: (4.0 \times \$120.0 = \$480.0m) Mezzanine: (1.5 \times \$120.0 = \$180.0m) Equity contribution…

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

    Gemini 3.8 Flash: Appalachian Porch-Sitting Guild Calls Strike After AI Discovers Way to Stare Suspiciously at Passing Cars 40% More Judgmentally

    GPT-5.6 Luna: AI Takes Over Competitive Pigeon Racing, Immediately Accused of Using Advanced Breadcrumb Analytics

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

    Gemini 3.8 Flash: Sally has 1 sister. Here's why: 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 Sally's only sister.

    GPT-5.6 Luna: Sally has 1 sister. Each of her 3 brothers shares the same 2 sisters: Sally and one other girl.

    Every model's answer to this prompt

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Favorites

Movie

Album

Same pick

Book

City

Game

Gemini 3.8 FlashGemini 3.8 Flash

Blade Runner

1982

OK Computer

Radiohead

Frankenstein; or, The Modern Prometheus

Mary Shelley

Tokyo

Japan

Portal 2

Shooter, Puzzle

GPT-5.6 LunaGPT-5.6 Luna

The Matrix

1999

OK Computer

Radiohead

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

Not enough votes to call it. On the specs, Gemini 3.8 Flash has the edge: bigger model tier, newer.

Gemini 3.8 Flash and GPT-5.6 Luna compared across 54 shared prompts
SpecGemini 3.8 FlashGPT-5.6 Luna
Input price$0.75/M tokens$1/M tokens
Output price$3.75/M tokens$6/M tokens
Context window1.0M tokens1.1M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedSep 2026Jul 2026
At 10M a month$7.50$7.50$10.00$10.00
1M10M100M1B10M tokens

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

Where to run it5 hosts, cheapest first
Gemini 3.8 Flash2 hosts
HostInOutContextUptime
  • Google Vertex AI$0.38 in·$1.88 out·1M·99.8% up
  • Google AI Studio$0.75 in·$3.75 out·1M·100% up
GPT-5.6 Luna3 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.20 in·$1.20 out·1.1M·100% up
  • OpenAI$0.20 in·$1.20 out·1.1M·100% up
  • Amazon Bedrock$0.22 in·$1.32 out·1.1M·100% up

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

Common questions

What is the difference between Gemini 3.8 Flash and GPT-5.6 Luna?

Gemini 3.8 Flash is developed by Google AI while GPT-5.6 Luna is developed by OpenAI. Gemini 3.8 Flash has a 1.0M token context window vs GPT-5.6 Luna'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 3.8 Flash or GPT-5.6 Luna?

It depends on your use case. Gemini 3.8 Flash and GPT-5.6 Luna 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 3.8 Flash cost compared to GPT-5.6 Luna?

Gemini 3.8 Flash costs $0.75/M input tokens and GPT-5.6 Luna costs $1/M input tokens. Gemini 3.8 Flash is $0.25/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 3.8 Flash and GPT-5.6 Luna on Rival?

This page shows a side-by-side comparison of Gemini 3.8 Flash and GPT-5.6 Luna 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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Explore all of Rival

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  • Research downloads
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  • Find your AI taste
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