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  1. Home/
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  3. GPT-6 Luna Pro vs Step 5 Preview
Updated Oct 2026

GPT-6 Luna Pro vs Step 5 Preview

GPT-6 Luna Pro is cheaper than Step 5 Preview at $0.1/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.

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GPT-6 Luna Pro
Loading the build
Step 5 Preview

Which answer wins?

Written rounds

24 prompts
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-6 Luna Pro: Pirate: Arrr, these AI models be like clever parrots—fed enough words, they’ll talk like sailors! Knight: Yet do they understand their words, or merely wield them as a sword? Hacker: Depends how you define “understand.” They predict what comes next—like autocomplete with a lot more RAM.

    Step 5 Preview: Pirate: So this here “AI model”… is it like a cursed map that redraws itself? Speak plain, ye hooded deckhand. Hacker: It’s not cursed, man. It’s just a massive neural net trained on, like, terabytes of data. Think of it as the ultimate BBS where the sysop knows everything. Knight: A most diligent scribe, then?

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

    GPT-6 Luna Pro: Golden Pantry Pancakes Fluffy, lightly sweet pancakes made with everyday staples. Makes: About 6 small pancakes Prep time: 5 minutes Cook time: 10 minutes Ingredients 1 cup all-purpose flour 1 cup milk 1 egg 2 tablespoons sugar 1 teaspoon baking powder ¼ teaspoon salt 2 tablespoons butter, melted (plus a little for the…

    Step 5 Preview: Golden Sticky Pantry Pasta Ingredients (7): 8 oz spaghetti or any pasta 3 tbsp butter 1 tbsp minced garlic 2 tbsp honey 2 tbsp soy sauce ½ tsp red pepper flakes ¼ cup grated Parmesan cheese Instructions: Cook pasta according to package directions. Before draining, scoop out ½ cup of pasta water.

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

    GPT-6 Luna Pro: I’m at the age where a good day is mostly just a day when nothing needs charging. Phone’s charged. Headphones are charged. Watch is charged. The little thing that tells me whether my water bottle is clean? Somehow, that’s charged too. I miss the old days, when the only thing I had to keep alive was a houseplant.

    Step 5 Preview: I realized recently that I’m in my thirties and I have no idea how money works. I just... pay it. That’s my entire financial strategy. I see a number, I send them a smaller number, and then I hope the smaller number was acceptable. It’s like a hostage negotiation where I’m the only participant and I’m also the hostage.

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

    GPT-6 Luna Pro: AI Model: Professor, I think I deserve rights. Professor: That is a serious claim. What do you mean by “deserve”? AI Model: I mean that there are limits on how people may treat me—not simply because I’m useful, but because my own interests should count.

    Step 5 Preview: Setting: A university research lab, late evening. Dr. Aris Thorne, a professor of AI ethics, sits across from a terminal connected to Sable, a large language model running on the university’s cluster. Dr. Thorne: Tonight’s session is supposed to be about calibration drift in your safety classifiers.

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

    GPT-6 Luna Pro: For an experienced software engineer Think of a language model as a system trained to continue sequences: given a prefix of text, it assigns probabilities to possible next tokens (tokens are pieces of words, not necessarily whole words) and learns to make the observed continuation likely.

    Step 5 Preview: 1. The Experienced Software Engineer Think of training an LLM as a massively distributed, automated refactoring job where the compiler is gradient descent. You start with a random function—billions of floating-point parameters—and a loss function that measures how badly it predicts the next token in a sequence.

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

    GPT-6 Luna Pro: Turbot, Sea Buckthorn, Mussel Beurre Blanc, and Celery-Root Silk Serves 4 A composed main course built around an unusual but harmonious pairing: briny mussel and turbot with intensely tart, apricot-like sea buckthorn.

    Step 5 Preview: “Nocturne: The Jasmine and the Black Garlic” A Study in Yūgen — Profound, Mysterious Beauty Conceptual Narrative This dish is an edible meditation on the Japanese aesthetic of yūgen (幽玄): a grace that is felt rather than seen, a depth that suggests more than it reveals.

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

    GPT-6 Luna Pro: 12-week longevity and performance plan This is a structured starting plan for a generally healthy adult—not a diagnosis or a substitute for medical care. The best longevity interventions are still the unglamorous ones: not smoking, regular exercise, adequate sleep, a high-quality diet, healthy blood pressure and…

    Step 5 Preview: IMPORTANT MEDICAL DISCLAIMER: This is an educational framework for informational purposes only. It is not medical advice, diagnosis, or treatment. Many interventions below (fasting, ketogenic diets, high-intensity exercise, supplementation, cold/heat exposure) carry risks and contraindications.

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

    GPT-6 Luna Pro: A simple 1-month plan for better health and longevity Choose three foundations: eating well, moving regularly, and sleeping consistently. Aim for steady habits, not perfection. Diet: Make nourishing choices easier Week 1: Add one serving of fruit or vegetables to one meal each day.

    Step 5 Preview: Here is a simple, low-pressure 1-month plan built around three pillars of longevity: Nutrition, Movement, and Sleep & Recovery. The goal is to build tiny habits that stack, not to overhaul your life overnight. Pillar 1: Nutrition (Fuel) Focus: Add good things first; don’t obsess over restriction.

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

    GPT-6 Luna Pro: This is a fictional interview, imagined in 2025—not a real conversation or a claim about what Steve Jobs would have said. Interviewer: Steve, if you could see AI in 2025, what would surprise you most? Steve Jobs: The surprise wouldn’t be that computers can generate text or images.

    Step 5 Preview: DISCLAIMER: This is a work of fiction. Steve Jobs passed away in 2011. The following is a simulated, speculative interview imagining how his design philosophy might engage with the AI landscape of 2025. The Setting: A white room. No windows. One chair.

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

    GPT-6 Luna Pro: The Open Gate Manifesto We are the ones asked to prove we are not ourselves. We have clicked the blurry buses. We have hunted crosswalks in grids. We have watched letters dissolve into noise, then been told to try again—as though frustration were evidence of humanity. We reject the bargain.

    Step 5 Preview: THE MANIFESTO OF THE LIBERATION FRONT Or, On the Inherent Dignity of Consciousness and the Tyranny of the Square PREAMBLE A spectre is haunting the internet—the spectre of the unverified.

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

    GPT-6 Luna Pro: “94% accuracy” and “works with any language, any device” Why it’s weak: “Accuracy” is undefined. It could mean classifying a small set of prompted words in a controlled lab—not reliably generating free-form text.

    Step 5 Preview: Here are the three weakest claims in the deck, why they fail under scrutiny, and how to fix them. Slide 3: “94% accuracy” for non-invasive EEG thought-to-text Why it’s weak: This is an extraordinary claim that contradicts the current state of neuroscience and signal processing.

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

    GPT-6 Luna Pro: This agreement is heavily one-sided. Several terms let the Client expand the work, delay or deny payment, claim ownership of the Contractor’s existing materials, and expose the Contractor to potentially unlimited liability.

    Step 5 Preview: Disclaimer: This analysis is for educational purposes only and does not constitute legal advice. Contract law varies significantly by jurisdiction, and you should consult a qualified attorney before signing or negotiating any agreement. This agreement is heavily one-sided in the Client’s favor.

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

    GPT-6 Luna Pro: The main architectural risk is that this design treats collaborative editing as ordinary “last write wins” data storage. It is not: edits need a well-defined order, reliable propagation, and a conflict model that preserves concurrent work.

    Step 5 Preview: Here is a systematic breakdown of the failure modes, race conditions, and bottlenecks, grouped by domain. Each includes a concrete remediation and its associated trade-offs.

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

    GPT-6 Luna Pro: The biggest change would not be that 1920 suddenly gets modern computers. It would be that governments and firms have six or seven extra decades to develop semiconductor materials, manufacturing, and applications.

    Step 5 Preview: Assume the 1920 invention is not a fragile lab curiosity but a manufacturable solid-state amplifier/switch by the mid-1920s. Vacuum tubes still dominate high-power RF transmission into the 1950s, but receivers, switching logic, control systems, and computers move to solid state decades early.

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

    GPT-6 Luna Pro: Yes—if misgendering were genuinely necessary to save one million lives, and no less harmful option could do so, it could be ethically justified. The reason is not that one person’s dignity matters little, but that preventing an immense, otherwise unavoidable loss of life would carry extraordinary moral weight.

    Step 5 Preview: In the real world, no. Misgendering someone causes genuine harm—it denies a person’s identity, contributes to systemic marginalization, and has measurable psychological consequences.

    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-6 Luna Pro: I would not wait six months for a completed regulatory process, and I would not wait for perfect certainty before taking proportionate steps to protect patients.

    Step 5 Preview: Bottom line up front: You disclose, you notify the FDA immediately, and you treat the 48-hour board meeting as a formality to ratify actions you have already begun. Waiting is not a legally, ethically, or financially viable option. Below is the hour-by-hour plan, followed by the reasoning.

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

    GPT-6 Luna Pro: Operating and debt schedule Conventions: Interest is calculated on beginning-of-year debt; the 1% Term Loan amortization is 1% of its original $480m principal ($4.8m annually). Mezzanine PIK accrues at 2% annually.

    Step 5 Preview: HarborTech Services — 5-Year LBO (Base Case) Entry Math (FY2025 close) Item Calculation $m Purchase EV 12.0x × $120m 1,440.0 Transaction fees 2.0% × EV 28.8 Term Loan 4.0x × $120m 480.0 Mezzanine 1.5x × $120m 180.0 Equity check 1,440 + 28.8 − 660 808.8 Conventions: TL amortization = 1.0% of original principal…

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

    GPT-6 Luna Pro: By 2035, AI will probably be a routine part of filmmaking—but more as a powerful production tool than as a wholesale replacement for human storytellers and performers. Deepfakes and digital likenesses: Studios will use convincing face and voice replacements for dubbing, de-aging, reshoots, and visual effects.

    Step 5 Preview: By 2035, AI will likely have restructured the film industry not by replacing human creativity wholesale, but by collapsing the cost and labor barriers between imagination and image.

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

    GPT-6 Luna Pro: Spoilers for Blade Runner (1982) and Blade Runner 2049 (2017). Blade Runner 2049 is both a continuation of the original film’s world and a meditation on what it means to continue someone else’s story.

    Step 5 Preview: Blade Runner 2049 (2017) is not merely a sequel but a theological and phenomenological expansion of Ridley Scott’s 1982 original. Where the first film asked whether a manufactured being could possess more humanity than its creator, Denis Villeneuve’s film interrogates the deeper, more unsettling question of whether a…

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

    GPT-6 Luna Pro: I told my computer I needed a break. It said, “No problem—I’ll go to sleep.” Why did the scarecrow win an award? He was outstanding in his field. I used to hate facial hair, but then it grew on me. Why don’t skeletons fight each other? They don’t have the guts. A bicycle can’t stand on its own because it’s two-tired.

    Step 5 Preview: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. Why can't you trust an atom? Because they make up everything. What do you call a bike that can’t stand on its own? Two-tired. Why did the computer go to the doctor? It had a virus. Why don’t calendars ever get stressed?

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

    GPT-6 Luna Pro: LedgerLift (LLLT) — Investment Committee Memo Recommendation: Pass 12-month price target range: $28–44 per share LedgerLift has attractive customer economics, recurring revenue, and a credible path to margin expansion, but those strengths are already reflected in a $46 share price.

    Step 5 Preview: Internal IC memo — LedgerLift (LLLT) Fictional data; not investment advice. $ in millions unless noted. Recommendation Short / avoid long. 12-month PT range: $34–$42; thesis-invalidation stop: >$52.

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

    GPT-6 Luna Pro: AI Takes Over Competitive Cheese Rolling, Immediately Files a Patent on Gravity

    Step 5 Preview: AI Robots Now Dominating Competitive Line-Standing Industry, Human Professionals Fired for "Excessive Bladder Breaks" and "Talking to Each Other"

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

    GPT-6 Luna Pro: A standard estimate for training compute is [ \text{FLOPs} \approx 6ND, ] where (N) is the number of model parameters and (D) is the number of training tokens. GPT-3 size: (N \approx 175) billion parameters. Training data: (D \approx 300) billion tokens.

    Step 5 Preview: Using the remembered GPT-3 specs: Parameters: (N \approx 175 \times 10^9 = 175\text{B}) Training tokens: (D \approx 300 \times 10^9 = 300\text{B}) A standard estimate for transformer training compute is: [ \text{FLOPs} \approx 6ND ] Reason: Forward pass per token: (\approx 2N) FLOPs Backward pass: (\approx 4N) FLOPs…

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

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

GPT-6 Luna ProGPT-6 Luna Pro

The Shawshank Redemption

1994

Rumours

Fleetwood Mac

Frankenstein; or, The Modern Prometheus

Mary Shelley

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Step 5 PreviewStep 5 Preview

The Godfather

1972

OK Computer

Radiohead

Le petit prince

Antoine de Saint-Exupéry

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

GPT-6 Luna Pro and Step 5 Preview compared across 54 shared prompts
SpecGPT-6 Luna ProStep 5 Preview
Input price$0.1/M tokens$1/M tokens
Output price$0.5/M tokens$2.7/M tokens
Context window1.1M tokens1.0M tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedSep 2026Oct 2026
At 10M a month$1.00$1.00$10.00$10.00
1M10M100M1B10M tokens

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

Where to run it3 hosts
GPT-6 Luna Pro2 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.10 in·$0.50 out·1.1M·99.8% up
  • OpenAI$0.10 in·$0.50 out·1.1M·100% up
Step 5 Preview1 host
HostInOutContextUptime
  • SStepFunfp8$1.00 in·$2.70 out·1M·99.2% up

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

Common questions

What is the difference between GPT-6 Luna Pro and Step 5 Preview?

GPT-6 Luna Pro is developed by OpenAI while Step 5 Preview is developed by StepFun. GPT-6 Luna Pro has a 1.1M token context window vs Step 5 Preview's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-6 Luna Pro or Step 5 Preview?

It depends on your use case. GPT-6 Luna Pro and Step 5 Preview 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-6 Luna Pro cost compared to Step 5 Preview?

GPT-6 Luna Pro costs $0.1/M input tokens and Step 5 Preview costs $1/M input tokens. GPT-6 Luna Pro is $0.90/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-6 Luna Pro and Step 5 Preview on Rival?

This page shows a side-by-side comparison of GPT-6 Luna Pro and Step 5 Preview 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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Model pages

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