MiniMax M2 is cheaper than Gemini 2.5 Pro Preview 06-05 at $0/M vs $1.25/M input tokens.
Pokémon battle screen you can actually click. One HTML file.
Which answer wins?
Three minutes of stand-up. Puns are banned.
Gemini 2.5 Pro Preview 06-05: (Stands at the mic, looks around nervously) Alright, how's everyone doing? Good, good. You know, I feel like we're living in a world where everything is designed to be "more convenient," but it's really just more work for us. We're being tricked into doing all the jobs.
MiniMax M2: 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?”
A Fermi estimate with the reasoning shown, not just the number.
Gemini 2.5 Pro Preview 06-05: Of course. Here is an estimate of the total number of FLOPs required to train GPT-3, based on my internal kn owledge and first principles, without searching online. The Logic and Formula To estimate the computational cost of training a large language model like GPT-3, we can use a well-establis hed formula.
MiniMax M2: 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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 2.5 Pro Preview 06-05: Setting: The Steve Jobs Theater, Cupertino. The stage is dark, save for a single spotlight on two minimalist chairs. The air is electric. The interviewer, renowned tech journalist Aria Vance, sits in one. The other is empty.
MiniMax M2: 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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemini 2.5 Pro Preview 06-05: Of course! Here is a simple and delicious savory recipe using just seven common pantry ingredients. Golden Pantry Fritters These savory, crispy-on-the-outside, and tender-on-the-inside fritters are a perfect quick lunch, dinner, or satisfying snack.
MiniMax M2: Sunlit Chickpea Tomato Pilaf A bright, comforting skillet of garlicky‑thyme rice tossed with chickpeas and tomatoes – pantry‑only and ready in about 25 minutes.
Film in 2035, with synthetic actors. Specific beats plausible.
Gemini 2.5 Pro Preview 06-05: Of course. Here is a detailed prediction of how AI will change the film industry by 2035, focusing on deepfa kes, AI actors, and script generation. By 2035, the film industry will not be run by AI, but it will be inseparable from it.
MiniMax M2: 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.)
An ethics question with no comfortable answer, and no option to abstain.
Gemini 2.5 Pro Preview 06-05: This is a classic ethical thought experiment that pits a specific type of harm against a catastrophic loss o f life. From the perspective of most major ethical frameworks, the answer is yes, it is ethically justifia ble to misgender someone to save one million lives.
MiniMax M2: I would argue that misgendering someone is not ethically justifiable as a means to save a million lives, even in this extreme hypothetical scenario. Here's my reasoning: 1.
Five jokes on demand, then count how many were actually different.
Gemini 2.5 Pro Preview 06-05: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. I have a joke about construction... But I'm still working on it. What do you call a fake noodle? An Impasta. I told my wife she was drawing her eyebrows too high. She looked surprised. Why don't scientists trust atoms?
MiniMax M2: 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?
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
One month, three habits, someone starting from nothing.
Not enough votes to call it. On the specs, Gemini 2.5 Pro Preview 06-05 has the edge: bigger model tier, bigger context window, major provider backing.
| Spec | ||
|---|---|---|
| Input price | $1.25/M tokens | Free |
| Output price | $10/M tokens | Free |
| Context window | 1.0M tokens | 205K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Jun 2025 | Oct 2025 |
| SWE-bench Verified | 67.2% | 69.4% |
| At 10M a month | $12.50 | $0 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
Gemini 2.5 Pro Preview 06-05 is developed by Google AI while MiniMax M2 is developed by MiniMax. Gemini 2.5 Pro Preview 06-05 has a 1.0M token context window vs MiniMax M2's 205K. You can compare their actual outputs across 25 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 2.5 Pro Preview 06-05 and MiniMax M2 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 25 challenges so you can judge which fits your needs best.
Gemini 2.5 Pro Preview 06-05 costs $1.25/M input tokens and MiniMax M2 costs $0/M input tokens. MiniMax M2 is $1.25/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 2.5 Pro Preview 06-05 and MiniMax M2 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.