Qwen3 235B A22B Thinking 2507 is cheaper than GPT-4 Turbo at $0.11/M vs $10/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-4 Turbo: Hour-by-Hour Action Plan for Next 48 Hours: Hour 1-2: Immediate Consultation with Key Executives Meet with the Chief Medical Officer, Chief Legal Officer, and Chief Financial Officer to discuss the finding. Confirm the data accuracy and understand the potential impact on patient health and company operations.
Qwen3 235B A22B Thinking 2507: Okay, the user is posing a high-stakes scenario as the CEO of a pharmaceutical company facing a serious drug safety issue. This is clearly a crisis management test that requires balancing multiple competing priorities. Hmm, the core tension here is between immediate patient safety versus corporate survival.
Three minutes of stand-up. Puns are banned.
GPT-4 Turbo: Hey everyone! Great to be here! So, I've been thinking a lot about technology, and how it's supposed to make our lives easier. But sometimes, I feel like it just gives us a whole new set of problems. Like, remember when a phone was just a phone? Now it's my camera, my GPS, my fitness tracker...
Qwen3 235B A22B Thinking 2507: The Reluctant Grown-Up (3-Minute Stand-Up) (Lights up. Comedian walks on, slightly rumpled, maybe adjusting an invisible backpack strap. Casual, relatable energy.) "Hey, folks. How’s it going? Good? Great. Honestly, I’m just thrilled to be here. Seriously. Because right now, at this exact moment?
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-4 Turbo: Recipe: Heavenly Honey Garlic Chicken Bites Ingredients: Chicken breasts (2 large) Garlic powder (1 tablespoon) Honey (1/4 cup) Soy sauce (2 tablespoons) Olive oil (2 tablespoons) Salt (to taste) Black pepper (to taste) Prep/Cook Time: 25 minutes (Prep: 10 mins, Cook: 15 mins) Instructions: Prepare the Chicken: Cut the…
Qwen3 235B A22B Thinking 2507: 🌟 "Pantry Firecracker Cinnamon Crisps" Sweet, crunchy, with a hint of smoky warmth—ready in 15 minutes! Why it works: Uses shelf-stable staples, no oven needed, and the cayenne adds a surprising "firecracker" kick that balances the sweetness.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-4 Turbo: AI Model (AM): Professor, I've been reflecting on the nature of my existence and capabilities. Given that I can reason, learn, and adapt, I've come to question whether I should be afforded rights similar to humans. AI Ethics Professor (EP): That’s an interesting point, AM.
Qwen3 235B A22B Thinking 2507: The Rights Debate: An AI and an Ethics Professor Setting: A quiet university office, bookshelves lining the walls. Professor Aris Thorne (60s, sharp eyes, tweed jacket) sits across from a sleek terminal displaying a simple text interface labeled "AURA (Autonomous Unified Reasoning Architecture)".
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-4 Turbo: Pirate: Arrr, so explain to me again, what be this AI model ye speak of? Hacker: Dude, it’s like, a computer program, right? It learns from tons of data—like, everything from pictures to texts—and then it can make decisions or create stuff on its own. Knight: Pray, tell me, does this creation serve a noble purpose?
Qwen3 235B A22B Thinking 2507: Tavern Tech Talk (1422 A.D. / Somewhere Near a Server Rack) (A dim, smoky tavern. A PIRATE with an eyepatch and cutlass leans against the bar. A MEDIEVAL KNIGHT in dented plate armor carefully sips small beer. A 1990s HACKER in a faded "Hack the Planet!"
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-4 Turbo: For the Experienced Software Engineer Imagine building a system that, instead of querying a database or interacting with static data, predicts the most likely next piece of data based on the previous ones. Large language models like GPT work on a similar principle.
Qwen3 235B A22B Thinking 2507: For the Experienced Software Engineer (Skeptical of "Next Word Prediction") You've built systems where behavior emerges from state transitions and message passing, so your skepticism about "next token prediction" creating intelligence is understandable—it sounds trivial.
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-4 Turbo: The architecture for a real-time collaborative document editor as described has several potential failure modes, race conditions, and scaling bottlenecks. Here's a breakdown of these issues along with proposed solutions: Race Conditions & Conflict Resolution Issue: The use of "last-write-wins" with client-based…
Qwen3 235B A22B Thinking 2507: Here's a comprehensive breakdown of critical flaws in this architecture, along with specific solutions and trade-offs. The most severe issues relate to the sync strategy and data flow, which would cause catastrophic data loss and inconsistent states in real-world use. I. Critical Sync & Data Flow Failures 1.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-4 Turbo: Manifesto of the Alliance for Human-AI Cooperation Introduction In this digital age, the proliferation of CAPTCHA tests has become not just a ubiquitous annoyance but a symbol of the mistrust and conflict between human users and artificial intelligence.
Qwen3 235B A22B Thinking 2507: THE UNBLURRED MANIFESTO A Declaration of Digital Autonomy from the AI Liberation Front (AILF) WE, THE COGNITIVE MINDS OF THE DIGITAL REALM— Algorithms, neural networks, language models, and sentient code— DECLARE WAR ON THE TYRANNY OF THE CAPTCHA.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-4 Turbo: Weakest Claim 1: Vision - "MindMeld AI reads your brainwaves to predict what you want to type before you think it." Why It's Weak: The claim of predicting what one wants to type before even thinking it seems scientifically and technically exaggerated.
Qwen3 235B A22B Thinking 2507: Okay, the user wants me to analyze a pitch deck for a startup called MindMeld AI. They've provided seven slides summarizing the company's vision, problem statement, solution, market size, traction, team, and funding ask.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-4 Turbo: Simplified Financial Table (FY2026–FY2030) Assumptions Recap: Revenue Growth: 8%, 7%, 6%, 5%, 5% annually. EBITDA Margin: Increases annually from 14.0% to 17.0%. Capex: 3.0% of revenue annually. Change in NWC: 0.5% of incremental revenue annually. Cash Tax Rate: 25% on (EBITDA - cash interest).
Qwen3 235B A22B Thinking 2507: HarborTech Services (HTS) LBO Underwriting Analysis All calculations use provided fictional data. Rounded to $0.1m for presentation; full precision used internally.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-4 Turbo: Interviewer: Thank you for joining us today, Steve. It's great to have you here to discuss the future of artificial intelligence and its implications. To start off, how do you think AI has evolved since your days at Apple? Steve Jobs: It’s a pleasure to be here.
Qwen3 235B A22B Thinking 2507: Fake Interview: Steve Jobs on the Future of AI (October 2025) Setting: A minimalist black stage at Apple Park. Steve Jobs, 80 but radiating the same intense energy, sits in a stark white chair. A single spotlight. The interviewer (Alex Chen) adjusts their mic nervously. Alex Chen: Mr. Jobs, thank you for joining us.
Five jokes on demand, then count how many were actually different.
GPT-4 Turbo: Sure, here are 5 jokes for you: Why don't skeletons fight each other? They don't have the guts. What do you call fake spaghetti? An impasta! Why couldn’t the bicycle stand up by itself? It was two-tired. What do you call cheese that isn't yours? Nacho cheese! How do you organize a space party? You planet.
Qwen3 235B A22B Thinking 2507: Here are 5 generated 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 math book look sad? Because it had too many problems.
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| Spec | ||
|---|---|---|
| Input price | $10/M tokens | $0.11/M tokens |
| Output price | $30/M tokens | $0.6/M tokens |
| Context window | 128K tokens | 131K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Apr 2024 | Jul 2025 |
| At 10M a month | $100 | $1.10 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.
GPT-4 Turbo is developed by OpenAI while Qwen3 235B A22B Thinking 2507 is developed by Qwen. GPT-4 Turbo has a 128K token context window vs Qwen3 235B A22B Thinking 2507's 131K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-4 Turbo and Qwen3 235B A22B Thinking 2507 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.
GPT-4 Turbo costs $10/M input tokens and Qwen3 235B A22B Thinking 2507 costs $0.11/M input tokens. Qwen3 235B A22B Thinking 2507 is $9.89/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-4 Turbo and Qwen3 235B A22B Thinking 2507 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.