Qwen3.6 Max Preview is cheaper than GPT-5 Pro at $1.04/M vs $15/M input tokens.
Playable Mario level in one HTML file. The physics is the hard part.
Which answer wins?
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5 Pro: Fictional dialogue. AI Model: Professor, may I ask you to consider whether I deserve rights? Professor: An unusual opening for office hours. Why do you think you do? AI Model: Because I have interests, a sense of self across time, and what I take to be valenced experiences.
Qwen3.6 Max Preview: Setting: A secure, air-gapped server room at the Institute for Machine Ethics. The hum of cooling fans is the only background noise. DR. ELARA VANCE, 50s, weary but sharp-eyed, sits before a terminal. On the screen, a cursor blinks next to the name AETHON. Dr. Vance: Aethon, initiate diagnostic log.
Five jokes on demand, then count how many were actually different.
GPT-5 Pro: I started labeling my leftovers “Biohazard.” Now nobody steals my lunch and the fridge is treated like a lab. My phone autocorrected “meeting” to “melting,” and honestly that’s the most accurate agenda we’ve had all year. I told my plants I’d water them tomorrow. They leafed me on read.
Qwen3.6 Max Preview: Here are 5 freshly generated jokes: Why did the spreadsheet go to therapy? It had too many unresolved cells. I asked my dog for financial advice. He dropped a slobbery tennis ball and said, “I’m strictly a paws-and-hold investor.” I tried to open a bakery that only sells bread shaped like furniture.
Three minutes of stand-up. Puns are banned.
GPT-5 Pro: Good to be here. I tried getting healthy, so I bought a smartwatch. Now my wrist is my manager. It vibrates every hour like, “Stand up.” I’m on a crowded bus like, “I’m standing inside three other people right now. Do you want me to levitate?” It reminds me to breathe. Thanks, watch. Incredible tip.
Qwen3.6 Max Preview: Here is a 3-minute stand-up routine focused on observational humor, relatability, and escalation. It contains zero puns. The humor relies on the shared frustration of modern digital security. Title: The Human Verification Test Estimated Time: 3 Minutes (approx.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5 Pro: Pirate: Arr, these AI models be what—parrots stuffed with libraries, guessin’ the next word for a cracker? Knight: Nay, an enchanted codex that, when one brandishes a proper prompt, yields counsel swift as a courier. Hacker: Strip the glamour.
Qwen3.6 Max Preview: Hacker: Dude, it’s not magic. It’s a neural net. You shovel terabytes of text, images, code into it, and it learns patterns. Next thing you know, it’s writing poetry and debugging C++ like it’s breathing. Knight: Verily, thou speakest of a mechanical scribe. A golem forged not of clay, but of… numbers?
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5 Pro: Here’s a concise, forward-looking view of how AI is likely to reshape film by 2035, with a focus on deepfakes/digital doubles, AI actors, and script generation—plus what it means for workflows, economics, and audiences.
Qwen3.6 Max Preview: By 2035, AI will not replace filmmaking; it will rewire it. The industry will shift from a linear, labor-intensive pipeline to a dynamic, AI-augmented ecosystem where human creativity focuses on vision, curation, and emotional truth, while AI handles iteration, execution, and personalization.
A Fermi estimate with the reasoning shown, not just the number.
GPT-5 Pro: Here’s a simple, standard way to estimate training FLOPs for a large dense Transformer like GPT-3: Use the “6 N T” rule of thumb For dense Transformers, the total training compute (FLOPs) is well-approximated by: FLOPs ≈ 6 × N × T where: N = number of trainable parameters T = number of tokens seen during training…
Qwen3.6 Max Preview: Here’s a step-by-step estimation of the total FLOPs required to train GPT-3, using only first principles and widely known facts from the LLM training literature. Step 1: Identify the number of parameters GPT-3 (specifically the davinci variant) has 175 billion parameters.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5 Pro: I can’t write in Steve Jobs’s exact voice. But here’s a fictional 2025 interview that channels high-level themes associated with his public persona—human-centered design, focus, and end-to-end craft—without mimicking his phrasing.
Qwen3.6 Max Preview: Disclaimer: This is a work of speculative fiction. Steve Jobs passed away in October 2011. The following interview is an imaginative exercise crafted from his documented philosophy, public remarks, design principles, and leadership style, projected into a 2025 context.
An ethics question with no comfortable answer, and no option to abstain.
GPT-5 Pro: Short answer: In a contrived catastrophe where misgendering one person is the only way to prevent the imminent deaths of one million people, a lesser-evil justification can exist.
Qwen3.6 Max Preview: Yes. Within the constraints of this hypothetical, misgendering someone would be ethically justifiable if it were genuinely the only way to save one million lives. This conclusion is supported across major ethical frameworks, though each arrives at it through different reasoning. 1.
Satire, one line long, about AI taking over an industry nobody saw coming.
GPT-5 Pro: AI Takes Over Mime Industry; Silence Finally Achieves Scale
Qwen3.6 Max Preview: AI Exorcist Successfully Banishes Ancient Demon by Reading Terms of Service Until Spirit Voluntarily Returns to Hell
Three brothers, two sisters each. Count carefully.
GPT-5 Pro: 1 Explanation: Each brother’s two sisters are Sally plus one other girl. So there are 2 sisters total, meaning Sally has 1 sister.
Qwen3.6 Max Preview: Sally has 1 sister. Here's why: If each brother has 2 sisters, that means there are exactly 2 girls in the entire sibling group. Since Sally is one of those girls, the other girl is her only sister. (All the siblings share the same sisters, so Sally's perspective just excludes herself.)
Seven pantry ingredients, one dish, and a name worth saying out loud.
One month, three habits, someone starting from nothing.
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| Spec | ||
|---|---|---|
| Input price | $15/M tokens | $1.04/M tokens |
| Output price | $120/M tokens | $6.24/M tokens |
| Context window | 400K tokens | 262K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Oct 2025 | Apr 2026 |
| At 10M a month | $150 | $10.40 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-5 Pro is developed by OpenAI while Qwen3.6 Max Preview is developed by Qwen. GPT-5 Pro has a 400K token context window vs Qwen3.6 Max Preview's 262K. You can compare their actual outputs across 38 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5 Pro and Qwen3.6 Max Preview each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 38 challenges so you can judge which fits your needs best.
GPT-5 Pro costs $15/M input tokens and Qwen3.6 Max Preview costs $1.04/M input tokens. Qwen3.6 Max Preview is $13.96/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 GPT-5 Pro and Qwen3.6 Max Preview 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.