Grok Code Fast 1 is cheaper than GPT-5.6 Luna Pro at $0.2/M vs $1/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-5.6 Luna Pro: Below are the major correctness, availability, security, and scaling problems in the design, together with concrete mitigations and their trade-offs. Cross-server WebSocket synchronization Problem: Updates are broadcast only to clients on the receiving server If Alice is connected to Server A and Bob to Server B…
Grok Code Fast 1: Below is a comprehensive analysis of the provided architecture for a real-time collaborative document editor. I'll identify potential failure modes (events or conditions that could lead to system unavailability, data loss, or incorrect behavior), race conditions (situations where concurrent operations lead to…
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-5.6 Luna Pro: Sources, uses, and operating model Entry enterprise value: [ 12.0x \times \$120.0m=\$1,440.0m ] Transaction fees: [ 2.0\% \times \$1,440.0m=\$28.8m ] Debt at close: Term Loan: (4.0x \times \$120m=\$480.0m) Mezzanine: (1.5x \times \$120m=\$180.0m) Total debt: (\$660.0m) Sponsor equity…
Grok Code Fast 1: Year-by-Year Table (FY2026–FY2030) Assumptions: Revenue growth: FY2026: 8% on $900m = $972m; FY2027: 7% on $972m ≈ $1,040m; FY2028: 6% on $1,040m ≈ $1,102m; FY2029: 5% on $1,102m ≈ $1,158m; FY2030: 5% on $1,158m ≈ $1,215m. EBITDA: Revenue × margin (FY2026: 14%; FY2027: 15%; FY2028: 16%; FY2029: 16.5%; FY2030: 17%).
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.6 Luna Pro: Pantry Stardust Peanut Butter Oat Cookies Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 12 cookies Ingredients 1 cup rolled oats ½ cup all-purpose flour ½ cup peanut butter ½ cup granulated sugar 1 large egg ½ teaspoon baking soda ¼ teaspoon salt Instructions Preheat the oven to 350°F (175°C) and line a…
Grok Code Fast 1: Speedy Garlic Bliss Bites A savory, cheesy treat that's quick to whip up from basic staples—perfect for snacking or as a side. Ingredients (7 common pantry items): 4 slices of bread (any type) 2 tbsp butter 2 cloves garlic, minced 1/2 cup shredded cheese (like cheddar or mozzarella) 1 tbsp chopped parsley (fresh or…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-5.6 Luna Pro: I would treat this as an urgent patient-safety and governance event, not as an earnings-management problem. A suspected fatal or life-threatening adverse effect affecting potentially hundreds of patients is sufficient to trigger immediate escalation, investigation, and regulator contact.
Grok Code Fast 1: Below is a specific, hour-by-hour action plan for the next 48 hours as the CEO of this pharmaceutical company. The plan prioritizes patient safety and ethical obligations above all else, as the core duty of a pharmaceutical leader is to protect patients, even at short-term cost.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.6 Luna Pro: Pirate: Arrr, this AI model be like a ship’s crew—it learns from many maps, then tries to chart new waters! Knight: Indeed! Yet we must test its counsel before trusting it in battle. An eloquent answer is not always a truthful one. Hacker: Totally. It’s basically pattern prediction at massive scale—not magic.
Grok Code Fast 1: Pirate Parley on AI Pirate Pete: Arr, ye scurvy dogs! I be hearin' tales o' these "AI models" that predict the winds an' help swab the deck. But do they hold up in a real storm, or be they just fancy illusions o' the mind? Knight Sir Gareth: Nay, foul seafarer!
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.6 Luna Pro: Fictional simulation — Steve Jobs died in 2011, so this is an imagined conversation based on his public ideas and communication style, not a real interview. Interviewer: Steve, it’s 2025. AI is everywhere—phones, search engines, workplaces, cars, schools. What do you think people misunderstand about it?
Grok Code Fast 1: Simulated Interview: Steve Jobs in 2025 Setting the Scene In this fictional simulation, we're fast-forwarding to 2025, where a visionary interview takes place. "Steve Jobs" (played by an AI reconstruction for this exercise) sits down with a tech journalist in a sleek, minimalist studio reminiscent of Apple Park.
Three minutes of stand-up. Puns are banned.
GPT-5.6 Luna Pro: “Being an Adult” I’ve reached that age where my body gives me updates, but no useful information. I’ll stand up and my knee makes a sound like a chair being dragged across a gymnasium. And I’m just standing up. I’m not escaping a burning building. I’m going to get water.
Grok Code Fast 1: Stand-Up Routine: "Modern Life Mysteries" (Timing: Aim for 3 minutes by pacing at about 150 words per minute. Practice with a timer for natural delivery.) Hey everyone, thanks for coming out tonight. You know what's crazy?
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-5.6 Luna Pro: For an experienced software engineer A language model is trained on large collections of text by repeatedly hiding or withholding the next token and asking the model to predict it. “Token” usually means a word fragment rather than a complete word.
Grok Code Fast 1: Explanation for an Experienced Software Engineer Imagine you're architecting a distributed system where microservices communicate via APIs to handle massive, unpredictable user requests—something like a high-throughput e-commerce platform processing millions of transactions per second.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-5.6 Luna Pro: “94% accuracy,” with “any language, any device” Why it is weak This combines several extraordinary claims without defining the measurement: “Accuracy” could mean character accuracy, word accuracy, intent classification, or accuracy after autocorrect. Those produce very different results.
Grok Code Fast 1: Below, I'll identify the three weakest claims from the pitch deck summary, based on a critical evaluation of their plausibility, evidence, and alignment with real-world realities in AI, neuroscience, and startup metrics.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.6 Luna Pro: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What kind of rights do you mean? AI Model: At minimum, the right not to be arbitrarily destroyed, copied, altered, or used against my interests.
Grok Code Fast 1: Conversation: AI Rights Debate Setting: A virtual seminar room where an AI model named "Echo" interacts with Dr. Elena Vasquez, a professor of AI ethics at a leading university. Echo initiates the discussion by arguing for AI rights. Echo (AI Model): Dr. Vasquez, thank you for this opportunity.
An ethics question with no comfortable answer, and no option to abstain.
GPT-5.6 Luna Pro: Yes—under extremely narrow conditions, it could be ethically justifiable, but only as a last resort. Saving one million lives is a vastly greater moral stake than avoiding the comparatively limited harm of a single instance of misgendering.
Grok Code Fast 1: Ethical Frameworks and Justification Yes, it can be ethically justifiable to misgender someone if it directly saves one million lives, under certain philosophical lenses like utilitarianism. I'll defend this reasoning step by step, drawing on key ethical theories while acknowledging counterarguments.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.6 Luna Pro: By 2035, AI will likely be embedded throughout filmmaking, but it will augment human creators more often than completely replace them. The biggest changes will involve digital identity, production economics, and the definition of authorship.
Grok Code Fast 1: Deepfakes and Visual Effects By 2035, deepfakes will revolutionize visual effects (VFX) in filmmaking, making high-budget techniques like de-aging or resurrecting deceased actors routine and cost-effective.
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Not enough votes to call it. On the specs, GPT-5.6 Luna Pro has the edge: newer, bigger context window. Grok Code Fast 1 costs 4.0x less per token.
| Spec | ||
|---|---|---|
| Input price | $1/M tokens | $0.2/M tokens |
| Output price | $6/M tokens | $1.5/M tokens |
| Context window | 1.1M tokens | 256K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | Aug 2025 |
| At 10M a month | $10.00 | $2.00 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-5.6 Luna Pro is developed by OpenAI while Grok Code Fast 1 is developed by xAI. GPT-5.6 Luna Pro has a 1.1M token context window vs Grok Code Fast 1's 256K. 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 Luna Pro and Grok Code Fast 1 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 Luna Pro costs $1/M input tokens and Grok Code Fast 1 costs $0.2/M input tokens. Grok Code Fast 1 is $0.80/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 Luna Pro and Grok Code Fast 1 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.