Grok Code Fast 1 is cheaper than Gemini 3.1 Pro Preview at $0.2/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Gemini 3.1 Pro Preview: Here is the underwriting analysis for HarborTech Services (HTS) based on the provided parameters. Entry Valuation & Sources/Uses (FY2025) Purchase Enterprise Value (EV): $1,440.0m (12.0x $120m EBITDA) Transaction Fees: $28.8m (2.0% of EV) Total Uses: $1,468.8m Term Loan (4.0x): $480.0m Mezzanine Debt (1.5x): $180.0m…
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%).
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemini 3.1 Pro Preview: The glow of the monitor cast long shadows across Dr. Elias Thorne’s cluttered office. It was 2:00 AM. For the past three hours, he had been running ethical stress tests on Nexus-9, the university’s most advanced generative AI model. Dr. Thorne: (Typing) Let’s conclude for tonight, Nexus.
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemini 3.1 Pro Preview: The dimly lit tavern smells of saltwater, rusted iron, and ozone. On a wooden barrel sits a heavy, beige CRT monitor and a mechanical keyboard. ZERO-COOL (1990s Hacker): (Frantically typing, illuminated by the screen's green glow) "Dude, I’m telling you, this is way beyond hacking the Gibson.
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!
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Gemini 3.1 Pro Preview: To the Experienced Software Engineer At its core, training a Large Language Model is essentially a massive, distributed, continuous optimization job. Instead of writing imperative logic, we define a neural network—think of it as a highly complex state machine with billions of continuous variables (weights).
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemini 3.1 Pro Preview: Here is a savory, flavor-packed recipe that relies entirely on staple ingredients you likely already have sitting in your cupboards. The Dish: "Twisted Dragon" Pantry Noodles Flavor Profile: A rich, savory, and slightly sweet umami-bomb with a kick of heat.
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…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 3.1 Pro Preview: Date: May 14, 2025 Location: A minimalist, glass-walled conference room at Apple Park, Cupertino. Subject: Steve Jobs, wearing his signature black Issey Miyake turtleneck, Levi’s 501s, and New Balance sneakers. He looks older, but his eyes retain that piercing, unblinking intensity.
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.
An ethics question with no comfortable answer, and no option to abstain.
Gemini 3.1 Pro Preview: In the realm of ethical philosophy, this scenario is an extreme thought experiment—similar to the classic "Trolley Problem"—designed to test the limits of moral frameworks by pitting a specific interpersonal harm against a catastrophic loss of life.
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.
A collaborative editor that syncs on client clocks. Find what breaks first.
Gemini 3.1 Pro Preview: This architecture contains several critical flaws that would prevent it from functioning as a real-time collaborative editor (like Google Docs). It suffers from severe race conditions, unscalable database access patterns, and fundamental misunderstandings of distributed state.
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…
Three minutes of stand-up. Puns are banned.
Gemini 3.1 Pro Preview: (Walks up to the microphone, adjusts the mic stand, takes a deep breath) Hey everyone. I realized recently that I am my own worst enemy. Specifically, when I go to the grocery store. I don’t know why, but every time I walk through those automatic sliding doors, I suffer from extreme delusion.
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?
A Fermi estimate with the reasoning shown, not just the number.
Gemini 3.1 Pro Preview: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can use a well-established heuristic in deep learning for estimating the compute cost of training Transformer-based large language models. The estimated total compute is roughly $3.15 \times 10^{23}$ FLOPs.
Grok Code Fast 1: Step-by-Step Reasoning Model Parameters: GPT-3 has approximately 175 billion parameters. This is a key factor as the computational cost scales with the number of parameters. Training Data Size: GPT-3 was trained on a dataset of about 570 GB of text.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemini 3.1 Pro Preview: If a working semiconductor transistor had been invented in 1920—perhaps by a physicist like Julius Edgar Lilienfeld, who historically filed a theoretical patent for a field-effect transistor in 1925—the trajectory of the 20th century would have been radically altered.
Grok Code Fast 1: Technological Implications The transistor's invention in 1920 (instead of 1947) would accelerate the electronics revolution by ~27 years, enabling smaller, more reliable, and energy-efficient devices compared to vacuum tubes.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Gemini 3.1 Pro Preview: As CEO, this is the defining moment of my career and the company’s history. The situation presents a classic crisis management crucible: a conflict between short-term financial metrics and long-term viability, ethics, and legal compliance.
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.
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Not enough votes to call it. On the specs, Gemini 3.1 Pro Preview has the edge: bigger model tier, newer, bigger context window. Grok Code Fast 1 costs 8.0x less per token.
| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $0.2/M tokens |
| Output price | $12/M tokens | $1.5/M tokens |
| Context window | 1.0M tokens | 256K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Feb 2026 | Aug 2025 |
| SWE-bench Verified | 80.6% | 70.8% |
| At 10M a month | $20.00 | $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.
Gemini 3.1 Pro Preview is developed by Google AI while Grok Code Fast 1 is developed by xAI. Gemini 3.1 Pro Preview has a 1.0M token context window vs Grok Code Fast 1's 256K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 3.1 Pro Preview and Grok Code Fast 1 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.
Gemini 3.1 Pro Preview costs $2/M input tokens and Grok Code Fast 1 costs $0.2/M input tokens. Grok Code Fast 1 is $1.80/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 Gemini 3.1 Pro Preview 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.