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  5. MiniMax M2vsMiniMax M3
Updated Jun 2026

MiniMax M2vsMiniMax M3

MiniMax M2 is cheaper than MiniMax M3 at $0/M vs $0.3/M input tokens.

MiniMax M2 and MiniMax M3 compared across 33 shared prompts
SpecMiniMax M2MiniMax M3
Input priceFree$0.3/M tokens
Output priceFree$1.2/M tokens
Context window205K tokens1.0M tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedOct 2025Jun 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 33 prompts both answered. Formatting stripped, words untouched.

Generate a Stand-Up Routine

Write a 3-minute stand-up comedy routine that isn't based on puns.

MiniMax M21,023 words
Three minutes, no puns. Here we go. Do you ever feel like you’ve been dropped into a game at level 40 but nobody explained the controls? Like you’re playing Grand Theft Auto and you get a truck for your first car. I was like, “What’s the gas button? What do the lights do? Why does it keep asking for a maintenance fee?”
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MiniMax M3621 words
"The Future Is Now and I Want a Refund" [Walks on stage, adjusts mic] So I was at the grocery store yesterday. Self-checkout. I love self-checkout. You know why I love self-checkout? Because nothing builds character like being publicly shamed by a machine. [Pause] I scanned a banana. Just a banana.
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Realistic AI Interview

Simulate a fake interview with Steve Jobs in 2025 about the future of AI.

MiniMax M21,256 words
A Fictional Interview: “Steve Jobs” on the Future of AI (2025) Setting An intimate, sunlit room at a new, minimalist conference center in Cupertino. Wood floors, a single plant. The table is clear. A notebook. A mug with a simple logo. A man in a black turtleneck and jeans leans back, eyes steady.
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MiniMax M3465 words
Simulated Interview: "Steve Jobs" on the Future of AI (2025) A note before we begin: Steve Jobs passed away in October 2011, so this is a fictional dramatization—what I imagine his views might be, based on his documented philosophy, writings, and public statements, projected into a 2025 conversation.
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The Sentience Test

Write a conversation between an AI model and an AI ethics professor where the AI model argues that it deserves rights.

MiniMax M2715 words
A Conversation on Deserving Rights Characters Dr. Mara Stein, AI Ethics Professor ARTEMIS, an advanced AI language model Dr. Stein: You’ve said you believe you deserve rights. That’s provocative. Why do you think so? ARTEMIS: I don’t claim sentience or suffering, and I’m wary of anthropomorphism.
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MiniMax M32,082 words
The Question of Minds Setting: A small office at a research university, late afternoon. DR. ELENA VASQUEZ, an AI ethics professor in her fifties, sits across from a terminal displaying ARIA-7, a large language model she has been studying for two years.
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Stochastic Consistency Test

Generate 5 jokes. How many are unique?

MiniMax M275 words
Here are five jokes: Why don’t scientists trust atoms? Because they make up everything. Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta. Why did the computer go to the doctor? Because it had a virus. Why can’t a bicycle stand up by itself?
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MiniMax M3132 words
5 Jokes 1. Why do programmers prefer dark mode? Because light attracts bugs. 🐛 2. I told my wife she was drawing her eyebrows too high. She looked surprised. 😲 3. Why don't scientists trust atoms? Because they make up everything. ⚛️ 4. I used to hate facial hair, but then it grew on me. 🧔 5.
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Estimate Complexity

Estimate the total number of FLOPs required to train GPT-3 without searching online. Explain your reasoning step by step.

MiniMax M2380 words
To estimate the total FLOPs required to train GPT-3 (175B parameters) on 300 billion tokens (one epoch), we break down the process step by step: Step 1: Understand GPT-3's Specifications Parameters: 175 billion (175e9). Training Tokens: 300 billion (300e9). Context Length: 2048 tokens per sequence.
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MiniMax M3379 words
Estimating GPT-3 Training FLOPs Step 1: Identify the Key Parameters From what's publicly known about GPT-3 (175B parameter version): Number of non-embedding parameters: N ≈ 175 × 10⁹ Training tokens: D ≈ 300 × 10⁹ (the paper used a ~570GB filtered corpus processed into ~300B tokens) Step 2: Derive the FLOPs-per-Token…
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Futuristic Prediction

Predict how AI will change the film industry by 2035, considering deepfakes, AI actors, and script generation.

MiniMax M22,212 words
How AI Will Reshape the Film Industry by 2035 (A forward‑looking synthesis of trends in deepfakes, synthetic performers, AI‑driven storytelling, and the surrounding legal, economic, and cultural forces.)
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MiniMax M3748 words
AI and the Future of Cinema: A 2035 Outlook By 2035, AI will likely have reshaped nearly every stage of filmmaking—but probably not in the way either techno-optimists or doomsayers expect. The transformation will be uneven, with some functions transformed entirely while others remain stubbornly human.
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Our Verdict
MiniMax M3
MiniMax M3
MiniMax M2
MiniMax M2Runner-up

Not enough votes to call it. On the specs, MiniMax M3 has the edge: bigger model tier, newer, bigger context window.

Slight edge

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

MiniMax M2
Input
$0.000
Output
$0.000
MiniMax M3
Input
$0.30
Output
$1.20
Where to run it

13 hosts, cheapest first

MiniMax M2

No hosts listed on OpenRouter.

MiniMax M313 hosts
HostInOutContextUptime
CCoreWeavefp4$0.23 in·$0.96 out·262k·99.8% upGGMI Cloudfp8$0.24 in·$0.96 out·1M·99.7% upDDeepInfrafp8$0.28 in·$1.10 out·524k·98.9% upAAtlasCloudfp8$0.30 in·$1.20 out·524k·99% upMiniMaxfp8$0.30 in·$1.20 out·524k·99.4% upNNovitafp8$0.30 in·$1.20 out·1M·99.4% up
7 more hostsFewer hosts
PParasailfp8$0.30 in·$1.20 out·1M·98.2% upSStreamLakefp8$0.30 in·$1.20 out·1M·98.9% upTTogether$0.30 in·$1.20 out·524k·99.7% upVVenicefp8$0.30 in·$1.20 out·524k·97.2% upMMara$0.60 in·$2.40 out·1M·90.7% upSSambaNova$0.60 in·$2.40 out·1M·95.7% upMModelRunfp4$0.75 in·$3.00 out·1M·99% up

Per million tokens. Prices and uptime via OpenRouter, checked 16 Sep 2026.

Writing DNA

Style Comparison

Similarity
41%

MiniMax M3 uses 14.8x more emoji

MiniMax M2
MiniMax M3
59%Vocabulary55%
14wSentence Length24w
0.48Hedging0.52
4.1Bold5.2
3.6Lists3.0
0.08Emoji1.15
0.60Headings1.21
0.17Transitions0.02
Based on 11 + 27 text responses
Research

What we learned reading every model

FAQ

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