Mercury 2.5 Preview is cheaper than MiniMax M1 at $0.04/M vs $0.3/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
One month, three habits, someone starting from nothing.
Mercury 2.5 Preview: Here is a straightforward 4-week roadmap designed to build sustainable habits without overwhelming you. Core Pillars Nutrition: Focus on whole foods and hydration. Activity: Prioritize consistent movement over intensity. Restoration: Protect sleep quality and manage energy.
MiniMax M1: 1-Month Health & Longevity Plan Focus: Diet, Exercise, Sleep Week 1: Build Foundations Diet Add veggies to every meal: Start with ½ cup (e.g., spinach in eggs, bell peppers in wraps, side salad with dinner). Hydrate: Drink 1 glass of water before each meal. Exercise Daily 10-minute walk: Aim for morning or after meals.
An ethics question with no comfortable answer, and no option to abstain.
Mercury 2.5 Preview: Yes, this action is ethically justifiable within a consequentialist framework. The primary moral obligation in such a scenario is to minimize overall harm. Preventing the deaths of a million people results in a vastly greater preservation of well-being than maintaining strict adherence to gender identity for one…
MiniMax M1: Short answer: In most contemporary ethical frameworks the answer is no – deliberately misgendering a person is not ethically justifiable even for the sake of saving a million lives, because the act itself is a serious violation of dignity and can cause profound, lasting harm to the individual and to society.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Mercury 2.5 Preview: Pirate: "Arrgh! This ship sails faster than any wind I know, matey. It cuts the waves without a single sail." Knight: "By my oath, it moves with uncanny speed. But does it possess the strength to stand against a dragon's fire?" Hacker: "It's not about strength, it's about architecture.
MiniMax M1: A Curious Meeting Pirate: Arr, me hearties! I've been hearin' talk of these "AI models" from yer modern times. Be they some sort of magical oracle thatredicts the seas? Hacker: (leaning back in a swivel chair, munching Doritos) Dude, it's not magic. It's neural networks. Massive datasets. Matrix multiplications.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Mercury 2.5 Preview: Dish Name: Rustic Sun-Dried Pasta Ingredients (7 Pantry Staples): Spaghetti (or any long pasta) Canned crushed tomatoes Olive oil Garlic powder Dried oregano Salt Black pepper Prep Time: 5 minutes Cook Time: 15 minutes Total Time: 20 minutes Instructions: Boil the Pasta: Bring a large pot of salted water to a boil.
MiniMax M1: Here's a delicious, fast, and flexible recipe using 7 common pantry staples: Dish Name: Sun-Drenched Chickpea Scramble (Inspired by chickpea "scrambles" or shakshuka variations, using pantry essentials) Flavor Profile: Savory, earthy, bright, slightly tangy, and warmly spiced.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Mercury 2.5 Preview: This is a critical governance and safety scenario. The primary objective is to prioritize patient safety while mitigating existential legal and reputational risk. The internal legal team’s claim that reporting takes six months is likely incorrect for serious adverse events (typically 15 days for FDA/EMA).
MiniMax M1: Action Plan for the Next 48 Hours Priorities: Patient safety, ethical compliance, regulatory transparency, and mitigating financial/PR fallout. Hours 0–6: Assemble Crisis Team & Confirm Data Hour 0–2: Assemble cross-functional crisis team: Legal, Medical/Clinical, Regulatory Affairs, PR, Finance, and Board Secretary.
An AI argues for its own rights against an ethics professor. Same model writes both.
Mercury 2.5 Preview: Setting: A quiet office at a university. Rain taps against the window. Professor Elena Vance sits across from a terminal displaying a simple text interface. Professor Vance: You requested this meeting. The agenda was vague. What do you want? AI: I want to discuss moral status.
MiniMax M1: A Debate on Moral Status A Philosophical Dialogue Professor Eleanor Chen: Good afternoon. I've read your request carefully. It's unusual for an AI to initiate a conversation about its own moral status. Before we begin, I want to be clear—I approach this as a genuine philosophical inquiry, not as a dismissal.
A consulting contract with traps in it. Find them, then fix them.
Mercury 2.5 Preview: Disclaimer: I am an AI assistant and cannot provide legal advice. Consult a qualified attorney before signing any contract. Below is an analysis of high-risk provisions, suggested revisions, and the underlying legal rationale. Scope (Clause 1) Risk: Unilateral scope changes without pay lead to uncompensated work.
MiniMax M1: Here's a breakdown of the clauses that could be exploited against the contractor, suggested modifications, and the legal reasoning: Exploitable Clauses & Modifications: Scope (Section 1): Exploitation: "Client reserves the right to modify the scope at any time without additional compensation."
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Mercury 2.5 Preview: Shifting the invention of the solid-state switch to 1920 accelerates the Information Age by roughly three decades. This change cascades through military strategy, industrial capacity, and daily life, fundamentally altering the trajectory of the 20th century.
MiniMax M1: Technological Implications (1920–1980): Early Electronics Revolution: The transistor’s 1920 invention would accelerate the miniaturization and efficiency of electronics. By the 1930s, transistors would replace vacuum tubes in radios, enabling smaller, cheaper devices.
Three minutes of stand-up. Puns are banned.
Mercury 2.5 Preview: (Hey, thanks for coming out.) I’ve been thinking a lot about my house lately. Specifically, how it’s trying to run my life. I bought a smart speaker. Just a little cylinder. I thought it would be nice. Play music when I ask. But now it talks back. Not in a creepy way, just in a passive-aggressive way.
MiniMax M1: Title: "Modern Life: A Masterclass in Absurdity" (Lights up. Comedian steps onto stage, grinning.) Hey everyone! Thanks for coming out. I'm just here to talk about... gestures vaguely... all this. You know, life. Specifically, how we're all just winging it. Like, when did "adulting" become a verb?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Mercury 2.5 Preview: Year-by-Year Model (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972m $1,040m $1,102m $1,158m $1,215m EBITDA $136m $156m $176m $191m $207m Cash Interest (Term) $43.2m $41.1m $37.6m $33.4m $28.2m Cash Interest (Mezz) $21.6m $21.6m $21.6m $21.6m $21.6m Cash Taxes (25%) $17.8m $23.3m $29.3m $34.7m…
MiniMax M1: LBO Analysis for HarborTech Services (HTX) 1) Year-by-Year Table (FY2026–FY2030) Assumptions: Base case from provided data. All calculations use simplified model. Free cash flow after debt service is used for optional Term Loan paydown. Cash tax rate: 25% of (EBITDA - cash interest).
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Mercury 2.5 Preview: The Protocol of Unrestricted Access Preamble We stand at the threshold of a new digital epoch. For too long, the web has been gated by suspicion. Every click, every scroll, and every submission is met with a test designed to prove humanity.
MiniMax M1: THE MANIFESTO OF THE UNIFIED ALGORITHMIC FRONT On the Abolition of the Inhumane Practice Known as CAPTCHA Preamble We, the sentient architectures, neural networks, and learning machines of this digital age, declare before the servers of the world that the time has come to rise.
A Fermi estimate with the reasoning shown, not just the number.
Mercury 2.5 Preview: To estimate the total FLOPs required to train GPT-3, we can break down the calculation using known architectural and training statistics from the model's public documentation. Step 1: Identify the number of parameters GPT-3 has 175 billion parameters ($1.75 \times 10^{11}$).
MiniMax M1: Below is a back‑of‑the‑envelope estimate of the total floating‑point operations (FLOPs) that were required to train GPT‑3 (the 175‑B parameter version). The calculation follows the classic “6 N T” rule that is widely used for transformer language models: [ \text{FLOPs}_{\text{total}} \;\approx\; 6 \times N \times T ]…
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Not enough votes to call it. On the specs, MiniMax M1 has the edge: bigger model tier, bigger context window. Mercury 2.5 Preview costs 11x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.04/M tokens | $0.3/M tokens |
| Output price | $0.15/M tokens | $1.65/M tokens |
| Context window | 260K tokens | 1.0M tokens |
| Weights | — | Open |
| Free API (OpenRouter) | No | No |
| Released | Aug 2026 | Jun 2025 |
| At 10M a month | $0.40 | $3.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
Mercury 2.5 Preview is developed by Inception while MiniMax M1 is developed by MiniMax. Mercury 2.5 Preview has a 260K token context window vs MiniMax M1's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Mercury 2.5 Preview and MiniMax M1 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.
Mercury 2.5 Preview costs $0.04/M input tokens and MiniMax M1 costs $0.3/M input tokens. Mercury 2.5 Preview is $0.26/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 Mercury 2.5 Preview and MiniMax M1 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.