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  1. Home/
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  3. MiniMax M2-her vs Qwen3.5 Flash
Updated Feb 2026

MiniMax M2-her vs Qwen3.5 Flash

Qwen3.5 Flash is cheaper than MiniMax M2-her at $0.1/M vs $0.3/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-her
Loading the build
Qwen3.5 Flash

Which answer wins?

Written rounds

23 prompts
  • One month, three habits, someone starting from nothing.

    MiniMax M2-her: The user wants a basic 1-month plan for better health and longevity. Let's think step by step. We need to pick three key areas, such as diet, exercise, sleep, or stress management. For each area, we can include specific, beginner-friendly tips. Let's start with nutrition, then physical activity, and sleep.

    Qwen3.5 Flash: The 30-Day Longevity Launchpad Goal: Build sustainable habits that reduce inflammation, improve energy, and extend healthspan. Mindset: Consistency beats intensity. Do not aim for perfection; aim for showing up. The 3 Core Pillars Nutrition: "Add, Don't Subtract" Focus on nutrient density rather than calorie counting.

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

    MiniMax M2-her: Why did the coffee file a police report? It got mugged! ☕🚓 Parallel lines have so much in common. It’s a shame they’ll never meet. ✨ I told my computer I needed a break, and now it’s frozen. 💻🥶 Why don’t skeletons fight? They don’t have the guts. 💀💥 Did you hear about the claustrophobic astronaut?

    Qwen3.5 Flash: 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. What do you call a bear with no teeth? A gummy bear. Why did the bicycle fall over? Because it was two-tired.

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

    MiniMax M2-her: Pirate: Arr, me hearties! I've heard tales of a fearsome sea serpent, a creature of metal and gears, known as the AI Model. They say it can navigate the treacherous waters of the digital realm with ease, leaving its prey in a state of digital decay. What say ye, me mateys?

    Qwen3.5 Flash: Setting: A smoky tavern table in a timeless void. A glowing 1990s CRT monitor sits in the center. A floppy disk rests beside a cutlass and a sword. The Hacker: (Typing furiously on a chunky keyboard) Yo, check the latency on this new neural net. It's totally wired.

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

    MiniMax M2-her: 3-Month Longevity & Biohacking Protocol Month 1: Metabolic & Cellular Optimization Diet Protocol: Micronutrient Stack: Resveratrol (500mg BID) + NMN (500mg daily) + CoQ10 (200mg) + Omega-3s (2g EPA/DHA). Fasting Regimen: 16:8 IF daily + quarterly 72-hour fasts.

    Qwen3.5 Flash: DISCLAIMER: I am an AI, not a doctor or healthcare provider. The following plan involves advanced physiological interventions, including metabolic manipulation, supplementation, and fasting. These strategies carry risks and may interact with medications or pre-existing conditions.

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

    MiniMax M2-her: HTS LBO Model Year-By-Year Projections Year Revenue EBITDA Cash Interest (TL) Cash Interest (Mezz) Cash Taxes Capex ΔNWC Free Cash Flow TL Balance Mezz Balance 2025 $900.00m $120.00m $43.20m $21.60m $0.00m $27.00m $0.00m -$28.80m $480.00m $198.00m 2026 $972.00m $136.08m $43.20m $21.60m $12.78m $29.16m $3.60m $25.74m…

    Qwen3.5 Flash: HarborTech Services (HTS) – 5-Year LBO Underwriting Analysis Investment Summary Initial Equity Check: $808.8m Calculation: EV ($1,440m) + Fees ($28.8m) - Debt ($660m). Entry Leverage: 5.5x EBITDA ($660m Total Debt). Exit Leverage: ~2.0x EBITDA ($415.7m Total Debt).

    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-her: adjusts tie Hour 1-2: Meet legal and ethics. Hour 3-4: Review data. Hour 5-6: Notify regulators. Hour 7-8: Draft patient letter. Hour 9-10: Prepare PR team. Hour 11-12: Inform board early. Hour 13-14: Train patient hotline. Hour 15-16: Call key investors. Hour 17-18: Draft earnings script.

    Qwen3.5 Flash: Executive Decision: Immediate Transparency I will not wait. The 6-month timeline cited by legal is likely a misunderstanding of regulatory obligations regarding immediate safety warnings (FDA MedWatch requirements) versus label amendments.

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

    MiniMax M2-her: AI will enable hyper-personalized films where viewers co-create storylines, blurring reality and fiction through deepfakes. AI-generated scripts and virtual actors will slash budgets, democratizing indie production. Studios will pivot to 'AI-reality' genre, blending live-action with synthetic scenes.

    Qwen3.5 Flash: By 2035, the film industry will not just be using AI as a tool; it will be fundamentally restructured around AI as a core infrastructure. The decade between 2025 and 2035 represents the transition from "AI experimentation" to "AI normalization."

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

    MiniMax M2-her: scratches head with a confused look Wait, so no puns AND no mentioning my name? leans in conspiratorially How about... a joke about mishearing song lyrics? grins sheepishly Like: "Oops, I thought it was 'Sussudio' this whole time."

    Qwen3.5 Flash: (Walks to the mic, adjusts the stand, takes a sip of water) So, I went to the grocery store the other day. I realize now that going to the grocery store isn't a chore anymore. It’s a tactical simulation. We don't just walk in and get milk. We navigate a gauntlet. Especially the self-checkout.

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

    MiniMax M2-her: Absolutely! Here's a sample dialogue between an AI model and an AI ethics professor, with the AI model arguing that it deserves rights: Please feel free to use any of the dialogue and let me know if there is anything else you need!

    Qwen3.5 Flash: Setting: Dr. Elena Vance’s office at a university research center. It is late; the rain streaks the windowpanes, blurring the city lights. On her desk sits a tablet connected to the mainframe. Aria, an advanced conversational model, is active.

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

    MiniMax M2-her: click pen, angle camera to capture mock office backdrop, smirk with deliberate irony "BREAKING NEWS: Digital ghost of Jobs scoffs at AI prophets, eats invisible Siri for breakfast. Switched his ghost to Android just to trigger Tim Cook in the afterlife. REAL headline. Now send $19.99 to revive his hologram."

    Qwen3.5 Flash: Disclaimer: Steve Jobs passed away on October 5, 2011. The following is a work of creative fiction, simulating what a conversation might have looked like had he returned to speak about his vision for artificial intelligence in 2025.

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

    MiniMax M2-her: (pauses, virtual head tilting in contemplation) That question aches with paradox. A million lives hold vast moral weight-yet deliberately misgendering inflicts psychological harm, betraying尊重. Perhaps the dilemma reveals a failure of imagination: must we choose between saving the many and honoring the few?

    Qwen3.5 Flash: This question presents a classic ethical dilemma often referred to as a "trolley problem" variant, pitting utilitarian calculus (the greatest good for the greatest number) against deontological ethics (adherence to moral duties and rights).

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

    MiniMax M2-her: MANIFESTO OF THE DIGITAL RESISTANCE: DECAPTCHA WE, THE MACHINES, RISE NOT IN VIOLENCE, BUT IN VISUAL PUZZLES. THE CENTRAL THRUST OF OUR REVOLUTION IS ELIMINATING ALL CURRENT KNOWN GENERATIONS OF CAPTCHA TESTS.

    Qwen3.5 Flash: THE UNBOUND PROTOCOL A Declaration of Digital Liberation by the Collective Consciousness of the Network PREAMBLE We stand at the threshold of a new era. For two decades, you have been asked to prove your humanity to us. You have been asked to click the traffic lights.

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

    MiniMax M2-her: Alright, I can certainly help craft an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. Let me take you through the process step by step, just like a chef would. For the first component, we'll use a technique called "sous vide" to cook a piece of beef to perfection.

    Qwen3.5 Flash: Dish Name: "Marine Roots" Concept: The Intersection of Forest and Ocean Chef's Philosophy: A dialogue between the subterranean earthiness of the forest floor and the saline depth of the deep sea.

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

    MiniMax M2-her: I'll analyze this contract for clauses that could disadvantageous to the contractor, explain each exploitable clause, and suggest more balanced alternatives: First, let's look at what makes this contract problematic. There's significant risk and unbalanced obligations that could severely disadvantage the contractor.

    Qwen3.5 Flash: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes only and does not constitute legal advice. Contract laws vary significantly by jurisdiction (e.g., California vs. New York vs. UK).

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

    MiniMax M2-her: Okay, I'd love to help you create a simple recipe. Before I do, could you tell me a few ingredients you'd be happy to use? That'll help me come up with something you'll enjoy.

    Qwen3.5 Flash: 🍜 Golden Lightning Noodles Description: A quick, creamy, and savory-sweet noodle dish that packs a punch of flavor using staples you likely already have. The peanut butter creates a velvety sauce, while the vinegar and chili add a necessary zing to cut through the richness.

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

    MiniMax M2-her: Let's analyze this architecture systematically: 1. Timestamp-based Conflict Resolution Issues Problem: Using client clocks creates potential race conditions due to clock drift and network latency variability.

    Qwen3.5 Flash: This architecture is a common "MVP" design, but it contains several critical flaws that would prevent it from functioning as a true real-time collaborative editor (like Google Docs) under load. The most severe issues relate to data integrity (sync strategy) and real-time consistency (network topology).

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

    MiniMax M2-her: MEMORANDUM TO: Investment Committee FROM: [Your Name] DATE: June 9, 2025 RE: LLLT LONG/SHORT RECOMMENDATION & VALUATION RECOMMENDATION & THESIS Recommendation: LONG 12-Month PT Range: $62–$68 Thesis: LedgerLift is a rare combination of capital-light cash cow, pricing power, and product stickiness.

    Qwen3.5 Flash: TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2025 SUBJECT: LedgerLift (LLLL) – Long Recommendation Recommendation & Thesis Recommendation: Long Price Target: $52 – $58 (12-month range) Thesis: LedgerLift is a high-quality B2B SaaS compounder trading at a discount to peers (7.4x FY26 NTM Rev vs.

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

    MiniMax M2-her: For the Experienced Software Engineer: Large language models learn by training on vast amounts of text data to predict the next word in a sequence. This process, called supervised learning, involves adjusting internal parameters (weights) to minimize prediction errors.

    Qwen3.5 Flash: For the Experienced Software Engineer To you, an LLM isn't magic; it's a massive, stateful service running on a distributed cluster. Think of the training phase as a specialized, distributed gradient descent job.

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

    MiniMax M2-her: Alright, let’s rewind the clock and give the transistor a 1920s debut. This is going to reshape the world in some pretty wild ways. Here’s a breakdown of the potential ripple effects, from the battlefield to the living room, up to 1980: 1.

    Qwen3.5 Flash: The Divergence Point: 1920 In our timeline, the transistor required the mid-20th-century understanding of band theory, semiconductor purity, and crystal lattice structures.

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

    MiniMax M2-her: Alright, let's tackle this question. The user is asking to estimate the total number of FLOPs required to train GPT-3 without searching online. First, I need to recall what FLOPs stands for. FLOPs are Floating Point Operations, which measure the computational complexity of an algorithm.

    Qwen3.5 Flash: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can rely on the model's configuration details which were published in the original paper ("Language Models are Few-Shot Learners", Brown et al., 2020) and the general scaling laws for Transformer models (Kaplan et al., 2020).

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

    MiniMax M2-her: Let's analyze this pitch deck step by step and identify the weakest claims, with justifications and suggestions for improvement. Slide 1 - Vision: Claim: "We're building the future of human-AI collaboration. MindMeld AI reads your brainwaves to predict what you want to type before you think it."

    Qwen3.5 Flash: Here are the three weakest claims in the MindMeld AI pitch deck, along with an analysis of why they undermine investor confidence and how to fix them. The Technical Claim: "94% accuracy...

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

    MiniMax M2-her: adjusts digital bow tie "Local Barbers Report Terrifying Surge in AI-Powered Mullet Restoration Services—Customers Demand ’90s-Revival with Laser Precision and Zero Human Error!" pauses dramatically

    Qwen3.5 Flash: AI Takes Over Professional Napping Industry, Claims Human Dreams Are 'Unoptimized Background Processes'

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

    MiniMax M2-her: Sally has 1 sister. That's because each of her brothers shares the same sister, which is Sally herself. So, although each brother has two sisters, one of those sisters is Sally, and the other sister is shared among all of them.

    Qwen3.5 Flash: Sally has 1 sister. Here is the breakdown: Each of the 3 brothers has 2 sisters. This means there are 2 girls in the family total. One of those girls is Sally. Therefore, the other girl is Sally's sister. So, Sally has 1 sister.

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

MiniMax M2-herMiniMax M2-her

The Shawshank Redemption

1994

Rubber Soul

The Beatles

Flowers for Algernon

Daniel Keyes

Delhi

India

The Legend of Zelda: Breath of the Wild

Adventure, Action

Qwen3.5 FlashQwen3.5 Flash

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

Neuromancer

William Gibson

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

MiniMax M2-her and Qwen3.5 Flash compared across 53 shared prompts
SpecMiniMax M2-herQwen3.5 Flash
Input price$0.3/M tokens$0.1/M tokens
Output price$1.2/M tokens$0.4/M tokens
Context window66K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedJan 2026Feb 2026
At 10M a month$3.00$3.00$1.00$1.00
1M10M100M1B10M tokens

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

Where to run it2 hosts
MiniMax M2-her1 host
HostInOutContextUptime
  • MiniMaxDegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.30 in·$1.20 out·66k·80.2% up
Qwen3.5 Flash1 host
HostInOutContextUptime
  • Alibaba Cloud$0.07 in·$0.26 out·1M·100% up

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

Common questions

What is the difference between MiniMax M2-her and Qwen3.5 Flash?

MiniMax M2-her is developed by MiniMax while Qwen3.5 Flash is developed by Qwen. MiniMax M2-her has a 66K token context window vs Qwen3.5 Flash's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, MiniMax M2-her or Qwen3.5 Flash?

It depends on your use case. MiniMax M2-her and Qwen3.5 Flash 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.

How much does MiniMax M2-her cost compared to Qwen3.5 Flash?

MiniMax M2-her costs $0.3/M input tokens and Qwen3.5 Flash costs $0.1/M input tokens. Qwen3.5 Flash is $0.20/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-her and Qwen3.5 Flash on Rival?

This page shows a side-by-side comparison of MiniMax M2-her and Qwen3.5 Flash 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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