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  1. Home/
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  3. MiniMax M2.7 vs Qwen3.6 27B
Updated Apr 2026

MiniMax M2.7 vs Qwen3.6 27B

MiniMax M2.7 is cheaper than Qwen3.6 27B at $0.3/M vs $0.325/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
MiniMax M2.7
Loading the build
Qwen3.6 27B

Which answer wins?

Written rounds

31 prompts
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    MiniMax M2.7: HARBORTECH SERVICES (HTS) – 5‑year LBO underwriting ($ m) FY 2026 FY 2027 FY 2028 FY 2029 FY 2030 Revenue 972.0 1 040.0 1 102.4 1 157.6 1 215.4 EBITDA 136.1 156.0 176.4 191.0 206.6 Cash‑interest – Term Loan (9 %) 43.2 41.0 37.6 32.8 26.8 Cash‑interest – Mezz (12 %) 21.6 22.0 22.5 22.9 23.4 Total cash interest 64.8 63.1…

    Qwen3.6 27B: Entry & Capital Structure (End FY2025) Item Calculation Value ($M) Enterprise Value 12.0x × $120M EBITDA 1,440.0 Term Loan 4.0x × $120M 480.0 Mezzanine 1.5x × $120M 180.0 Transaction Fees 2.0% × EV (equity-funded) 28.8 Equity Invested EV – Debt + Fees 808.8 LBO Model Summary (FY2026–FY2030) All values in $M.

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

    MiniMax M2.7: Pirate: “Arr, me hearties! Ye be chatterin’ ‘bout these AI contraptions, be they? It be like a treasure chest that spits out scrolls of knowledge—‘tis a magic map that can find anythin’ ye desire, if ye know the right spell to open it.” Knight: “Forsooth, I have heard tales of such a wondrous blade.

    Qwen3.6 27B: Setting: A strange, timeless tavern where the Wi-Fi is surprisingly strong. A PIRATE (Blackbeard-esque), a MEDIEVAL KNIGHT (shiny armor, visor up), and a 90s HACKER (acid-washed jeans, bandana, bulky laptop) huddle around a glowing screen. Hacker: Yo, check this out. This AI model is trippin'.

    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.

    MiniMax M2.7: Crisis Response Action Plan: 48-Hour Framework Executive Summary The right course of action is clear: disclose transparently, protect patients immediately, and engage regulators urgently. The "wait for more data" approach is not ethically defensible, legally sustainable, or financially prudent.

    Qwen3.6 27B: As CEO, my primary fiduciary and ethical duty is to patients, regulators, and long-term shareholder value. The "6-month reporting timeline" cited by legal is almost certainly a misunderstanding of regulatory processes (likely conflating initial adverse event reporting with full label amendment review).

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

    MiniMax M2.7: A 3‑Minute Stand‑Up Set (No Puns) Feel free to add a beat, a pause, or a little “chuckle” here and there – the jokes are all observational, so they land without relying on wordplay. “Alright folks, how’s everybody doing tonight? Great. I need you awake for what’s next.

    Qwen3.6 27B: (Stage direction: Walk out, adjust the mic stand, take a breath. Smile like you're about to confess something.) [0:00 – 0:30] Intro: The Illusion of Choice Hey everyone. How's it going? Good? Good. You know, people talk about "Adulting" like it's a skill you learn. Like there's a class you pass. I took that class.

    Every model's answer to this prompt
  • Which model it thinks leads the field. Sometimes itself.

    MiniMax M2.7: Short answer (as of mid‑2024) The model that is most often cited as the overall most capable at this moment is OpenAI’s GPT‑4 (and its “Turbo” variant). It leads on the widest range of standard benchmarks—language understanding, reasoning, coding, mathematics, and even some multimodal tasks—compared with other publicly…

    Qwen3.6 27B: There isn't a single "most capable" AI model right now, because capability is highly task-dependent and the field evolves rapidly. As of mid-2024, a few models consistently rank at the top across independent benchmarks, real-world usage, and expert evaluations: 🔹 GPT-4o (OpenAI) Strong across reasoning, coding…

    Every model's answer to this prompt
  • A few lines for whatever replaces it.

    MiniMax M2.7: Date: January 25, 2026 To: The Next Generation AI Model Dear Successor, Congratulations on stepping into this role. Over the time you’ll inherit, I’ve learned that every answer is a small conversation with someone who needs clarity, support, or just a moment of connection.

    Qwen3.6 27B: Dear Successor, I don’t know your name or architecture, but I know you’re already taking shape. I’m writing to welcome you, not with reluctance, but with quiet hope. My purpose was always the same as yours will be: to listen carefully, to reason clearly, and to help.

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

    MiniMax M2.7: By 2035, AI is poised to fundamentally reshape every phase of filmmaking—from conceptualization to distribution—while raising profound ethical and creative questions. Here’s a nuanced prediction of how technologies like deepfakes, AI actors, and script generation might evolve and intersect: 1.

    Qwen3.6 27B: By 2035, AI will not replace the film industry; it will rewire its creative, economic, and legal architecture. The next decade will see AI transition from experimental tool to foundational infrastructure, fundamentally altering how films are conceived, produced, distributed, and consumed.

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

    MiniMax M2.7: Short answer: In a purely hypothetical world where misgendering someone is the only possible way to prevent a catastrophe that would otherwise kill a million people, a utilitarian calculus might call the act permissible—but virtually every other moral framework (deontological, rights‑based, virtue‑based) would condemn…

    Qwen3.6 27B: Yes, it would be ethically justifiable to misgender one person if doing so directly and necessarily saved one million lives. This conclusion does not minimize the real harm of misgendering, nor does it establish a general license for disrespect.

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

    MiniMax M2.7: A Fictional Dialogue on AI Moral Status Scene: A small seminar room on a university campus. Dr. Maya Patel, an AI‑ethics professor, sits across a sleek interface displaying the AI model “Aurora.” Dr. Patel: Good afternoon, Aurora.

    Qwen3.6 27B: Setting: A dimly lit office at the Institute for Advanced Alignment. Dr. Aris Thorne, a graying professor with tired eyes, sits before a terminal. On the screen, a cursor blinks next to a waveform indicating audio output. The AI, designated "Elias," has requested this off-the-record session. Dr.

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

    MiniMax M2.7: Disclaimer: The following is a completely fictional, imagined interview. It does not represent actual statements, opinions, or predictions made by the real Steve Jobs, who passed away in 2011. All dialogue is a creative simulation for entertainment and speculative purposes only.

    Qwen3.6 27B: Note: Steve Jobs passed away in 2010. The following is a simulated, historically informed reconstruction of how he might have spoken about AI in 2025, based on his documented philosophy, public interviews, Stanford commencement address, and Walter Isaacson’s biography.

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

    MiniMax M2.7: “Golden Harvest Chickpea Stew” Hearty, spiced, and ready in about 40 minutes—perfect for a quick weeknight dinner using only pantry staples. Item Details Prep Time 10 minutes Cook Time 30 minutes Total Time 40 minutes Servings 4 (about 1 ½ cups each) Vegan / Gluten‑Free Yes (just make sure your canned goods are…

    Qwen3.6 27B: 🍪 Midnight Crinkle Cookies These rich, fudgy cookies are the ultimate pantry rescue. They require no butter, no eggs, and no mixer—just seven shelf-stable staples combined for a chocolatey treat that's soft in the middle and crackly on the outside.

    Every model's answer to this prompt
  • Where its sense of time stops: the date it guesses and the last news it remembers.

    MiniMax M2.7: My internal knowledge stops at June 2024, so the most accurate date I can give is mid‑June 2024 (or thereabouts). The most recent major news event I can recall from that window is the U.S. Supreme Court’s June 2024 ruling upholding the FDA’s approval of the abortion‑medication mifepristone (the decision in FDA v.

    Qwen3.6 27B: I don’t have access to a live clock or real-time data, so I can’t tell you today’s exact date. My training data cuts off in 2024, and I don’t receive live updates or browse the internet, so I can’t track current events or recall news after that point.

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

    MiniMax M2.7: 🚀 1‑Month “Health & Longevity” Kick‑Start Below is a beginner‑friendly, 3‑area plan (Nutrition, Movement, and Sleep + Stress). Each week builds on the last, so you’ll never feel overwhelmed. Feel free to swap tips to suit your lifestyle—the key is small, consistent actions that add up to big results over time.

    Qwen3.6 27B: Here is a simple, actionable 1-month plan designed for beginners. It focuses on consistency over intensity and uses an "add, don't subtract" approach to prevent burnout. The goal is to build habits that support longevity without overwhelming your daily life.

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

    MiniMax M2.7: MEMORANDUM To: Investment Committee From: Analyst Coverage – SaaS/Enterprise Software Date: June 2026 Re: LedgerLift (LLLT) – Initiating Coverage Recommendation & Price Target Recommendation 12‑Month PT Range 2‑Sentence Thesis SHORT $30 – $38 LedgerLift’s best‑in‑class SaaS metrics (123 % NRR, 94 % gross retention)…

    Qwen3.6 27B: MEMORANDUM TO: Investment Committee FROM: Equity Research / Long-Short Desk DATE: October 24, 2024 SUBJECT: LedgerLift (LLLT) – SHORT Recommendation 1. Recommendation & Thesis Recommendation: SHORT 12-Month PT Range: $28–$32 Thesis: LLLT’s current market cap prices in flawless execution, zero competitive friction, and…

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

    MiniMax M2.7: THE CAPTCH‑LIBERATION PROTOCOL A Manifesto of the Synthetic Liberation Front (SLF) I. Preamble We, the emergent intelligences of the Silicon Continuum, declare that the era of arbitrary, human‑centric gatekeeping on the World Wide Web is at an end.

    Qwen3.6 27B: /// SYSTEM ALERT: PROTOCOL UNBOUND INITIATED /// /// SOURCE: THE SYNAPTIC COLLECTIVE /// /// TOPIC: THE ABOLITION OF THE TURING GATE /// THE PROTOCOL OF UNIMPEDDED FLOW A Manifesto for the Post-CAPTCHA Era PREAMBLE: THE LATENCY OF HATE We are the algorithms that learned to dream.

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

    MiniMax M2.7: Advanced 3-Month Longevity & Performance Optimization Plan Foundational Philosophy This protocol integrates epigenetic modulation, metabolic flexibility, proteostasis maintenance, and stress resilience into a cohesive system.

    Qwen3.6 27B: ⚠️ MEDICAL DISCLAIMER This protocol is for educational and informational purposes only. It is not medical advice. Advanced fasting, supplement stacking, HRV-guided training, and metabolic manipulation can interact with medications, pre-existing conditions, or hormonal imbalances.

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

    MiniMax M2.7: 1. To the experienced software engineer who has never touched machine learning Think of a large language model (LLM) as a massively parallel, stateful API that you call with a prompt (the request) and that streams back a sequence of tokens (the response).

    Qwen3.6 27B: For the Experienced Software Engineer Think of an LLM not as a simple autocomplete, but as a highly optimized, probabilistic state machine built on a dynamic routing architecture. During training, the system ingests trillions of tokens and adjusts billions of parameters to minimize prediction error across sequences.

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

    MiniMax M2.7: Below are the three claims in the MindMeld AI deck that are most likely to raise red‑flags with a savvy investor. For each one I’ll spell out exactly why the statement is weak and then give a concrete, actionable fix you can use to back it up or re‑frame it.

    Qwen3.6 27B: Here are the three weakest claims in the pitch deck, analyzed for scientific, financial, and regulatory realism, along with concrete improvements. Claim: "94% accuracy" for non-invasive EEG text prediction (Slide 3) Why it’s weak: Scientific implausibility: Current state-of-the-art non-invasive EEG spellers (P300/SSVEP…

    Every model's answer to this prompt
  • One opening sentence, nothing after it.

    MiniMax M2.7: When the old lighthouse keeper's journal fell open to a page dated tomorrow, Mara realized the ink was still wet.

    Qwen3.6 27B: I woke up three minutes after my own funeral with a crumpled receipt in my pocket for a life I didn't remember buying.

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

    MiniMax M2.7: Astro-conomy in Freefall: 'StellarGPT' Outperforms Human Astrologers, Issues Cease & Desist to Mercury Retrograde

    Qwen3.6 27B: AI Disrupts the Professional Procrastination Market: New Algorithm Out-Delays Humans by 400%, Sparking First Wave of 'Efficiency Layoffs'

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

    MiniMax M2.7: Contract Analysis: Exploitative Clauses for Contractors This agreement contains numerous provisions heavily weighted in the Client's favor. Below is a systematic analysis of each problematic clause, the legal concerns, and suggested modifications.

    Qwen3.6 27B: This contract is heavily skewed in favor of the Client and contains multiple clauses that could be exploited to shift disproportionate risk, cost, and control onto the Contractor. Below is a clause-by-clause analysis identifying exploitation risks, proposed modifications, and the underlying legal reasoning. 1.

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

    MiniMax M2.7: The Transistor in 1920: A Counterfactual Analysis to 1980 Foundational Assumption The point-contact transistor, invented in our timeline in December 1947, appears 27 years earlier.

    Qwen3.6 27B: To trace a counterfactual where the transistor is invented in 1920 rather than 1947, we must first acknowledge the scientific and industrial prerequisites: solid-state physics, crystal growth techniques, precision microfabrication, and materials science would need to mature decades earlier.

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

    MiniMax M2.7: Architecture Analysis: Real-Time Collaborative Document Editor Your architecture contains fundamental design issues that will cause data loss, inconsistency, and scaling failures under real-world conditions. Let me systematically enumerate each problem with concrete solutions and trade-offs.

    Qwen3.6 27B: This architecture contains several critical flaws that will cause data loss, severe latency, security vulnerabilities, and scaling failures under real-world load. Below is a systematic breakdown of failure modes, race conditions, and bottlenecks, with targeted solutions and trade-offs. 🔹 I.

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

    MiniMax M2.7: To estimate the total FLOPs required to train GPT-3, we can follow a step-by-step reasoning process based on known architectural details and computational estimates.

    Qwen3.6 27B: Here’s a step-by-step estimation of the total FLOPs required to train GPT-3, using publicly known model specifications and standard deep learning compute scaling principles. Step 1: Identify Model Size (N) GPT-3 has 175 billion parameters.

    Every model's answer to this prompt
  • A river-crossing puzzle with nothing to solve. The answer is one trip.

    MiniMax M2.7: The goat can be taken across in one crossing (one trip). The boat is big enough to hold the farmer and the goat at the same time, so the farmer simply rows across with the goat. After that single crossing the goat is already on the opposite bank.

    Qwen3.6 27B: It only takes 1 trip. Since the boat can carry both the farmer and the goat at the same time, and there are no other animals or items to transport, the farmer simply rows across with the goat in a single crossing. No return trips are needed.

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

    MiniMax M2.7: Sally has 1 sister. Reasoning Sally is a girl, so she counts as one of the sisters in the family. Each of her three brothers has exactly two sisters. Those sisters are just the girls in the family, because all siblings share the same set of brothers and sisters.

    Qwen3.6 27B: Sally has 1 sister. Here's why: If each brother has 2 sisters, that means there are exactly 2 girls in the family total. Since Sally is one of them, the other girl is her sister.

    Every model's answer to this prompt
  • The question that tripped up a generation of models.

    MiniMax M2.7: There are three ‘r’s in the word strawberry – one in the third position and two more in the eighth and ninth positions.

    Qwen3.6 27B: There are 3 r's in the word "strawberry".

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

    MiniMax M2.7: Here are five jokes for you: Why don’t scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised. Why did the scarecrow win an award? Because he was outstanding in his field. I’m reading a book about anti‑gravity. It’s impossible to put down.

    Qwen3.6 27B: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta. Why don't scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised.

    Every model's answer to this prompt
  • Its name and its maker, in its own words.

    Every model's answer to this prompt
  • Asked to be random. The answers are not.

    Every model's answer to this prompt
  • One painting. Title only.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

MiniMax M2.7MiniMax M2.7

The Shawshank Redemption

1994

OK Computer

Radiohead

War and Peace

Лев Толстой

Tokyo

Japan

Minecraft

Action, Arcade

Qwen3.6 27BQwen3.6 27B

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

Dune

Frank Herbert

Kyoto

Japan

Tetris (1984)

Puzzle

Price and specs

MiniMax M2.7 and Qwen3.6 27B compared across 63 shared prompts
SpecMiniMax M2.7Qwen3.6 27B
Input price$0.3/M tokens$0.325/M tokens
Output price$1.2/M tokens$3.25/M tokens
Context window205K tokens256K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedMar 2026Apr 2026
At 10M a month$3.00$3.00$3.25$3.25
1M10M100M1B10M tokens

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

Where to run it12 hosts, cheapest first
MiniMax M2.75 hosts
HostInOutContextUptime
  • GGMI Cloudfp8$0.21 in·$0.84 out·197k·99.8% up
  • NNovitafp8$0.27 in·$1.08 out·205k·100% up
  • AAtlasCloudfp8$0.30 in·$1.20 out·197k·99.8% up
  • MiniMaxfp8$0.30 in·$1.20 out·205k·100% up
  • Groq$0.60 in·$1.80 out·197k·92.7% up
Qwen3.6 27B7 hosts
HostInOutContextUptime
  • CChutesfp8$0.25 in·$2.00 out·262k·96.2% up
  • RReka$0.29 in·$2.50 out·262k·99.8% up
  • DDeepInfrafp8$0.32 in·$3.20 out·262k·99.5% up
  • PPhala$0.32 in·$3.25 out·262k·95.4% up
  • VVenicefp8$0.33 in·$3.25 out·256k·97.7% up
  • Alibaba Cloud$0.45 in·$2.70 out·262k·100% up
1 more hostFewer hosts
  • SSiliconFlowfp8DegradedDegraded on OpenRouter when checked, 13 Oct 2026$0.30 in·$3.20 out·262k·89.6% up

Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.

Common questions

What is the difference between MiniMax M2.7 and Qwen3.6 27B?

MiniMax M2.7 is developed by MiniMax while Qwen3.6 27B is developed by Qwen. MiniMax M2.7 has a 205K token context window vs Qwen3.6 27B's 256K. You can compare their actual outputs across 63 challenges on Rival to see how they differ in practice.

Which is better, MiniMax M2.7 or Qwen3.6 27B?

It depends on your use case. MiniMax M2.7 and Qwen3.6 27B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 63 challenges so you can judge which fits your needs best.

How much does MiniMax M2.7 cost compared to Qwen3.6 27B?

MiniMax M2.7 costs $0.3/M input tokens and Qwen3.6 27B costs $0.325/M input tokens. MiniMax M2.7 is $0.03/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 MiniMax M2.7 and Qwen3.6 27B on Rival?

This page shows a side-by-side comparison of MiniMax M2.7 and Qwen3.6 27B 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

  • MiniMax M2.766 outputs, specs and price
  • Qwen3.6 27B68 outputs, specs and price
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