Qwen3 235B A22B 2507 is cheaper than Gemini 4 Argon at $0.00015/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemini 4 Argon: Here is a recipe for a savory, restaurant-quality pasta dish that relies entirely on basic pantry staples. Midnight Sun Pasta (Crispy Garlic & Tomato Spaghetti) This dish gets its name from the golden-red sauce created by slow-cooking garlic and tomato paste, and the fact that it’s the ultimate quick meal to whip up…
Qwen3 235B A22B 2507: Dish Name: Golden Garbanzo Drizzle A cozy, savory-spiced chickpea stew with a honey-lime finish — simple, satisfying, and ready in minutes. Ingredients (7 common pantry staples): 1 can (15 oz) chickpeas (garbanzo beans), drained and rinsed 1 can (15 oz) diced tomatoes (undrained) 2 tbsp olive oil 1 tsp ground cumin ½…
Five jokes on demand, then count how many were actually different.
Gemini 4 Argon: Here are 5 jokes for you: Why don’t scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. How do you organize a space party? You planet. What do you call a bear with no teeth? A gummy bear.
Qwen3 235B A22B 2507: Sure! Here are 5 original jokes: I asked my dog what's two minus two. He said nothing. (Paw-sitively nothing!) Why did the coffee file a police report? It got mugged. Every single morning. I used to be a baker, but I couldn't make enough dough. So I switched careers and became a plumber. Now I deal with real pipes.
Three-star dish, one unusual pairing, plating described in full.
Gemini 4 Argon: Dish Name: "Submerged Forest" Dry-Aged Diver Scallop, Bone Marrow Caramel, Roasted Koji & Pine Nut Pruina, Fermented Spruce Tip Emulsion, and Cured Pine Cone Scales The Conceptual Narrative "Submerged Forest" explores the collision of two seemingly disparate ecosystems: the cold, abyssal depths of the ocean and the…
Qwen3 235B A22B 2507: Dish Title: Ember & Petal – A Dialogue Between Earth and Sky Conceptual Narrative: Inspired by the elemental contrast between volcanic resurgence and alpine serenity, Ember & Petal explores the tension and harmony of opposing natural forces through taste, texture, and temperature.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 4 Argon: Title: The Bicycle and the Brain: Steve Jobs on the AI Revolution Date: October 14, 2025 Location: The Steve Jobs Theater, Apple Park, Cupertino, CA Interviewer: Kara Swisher (The stage is bare except for two leather armchairs and a small glass table with two bottles of SmartWater. Steve Jobs walks out.
Qwen3 235B A22B 2507: Title: "A Vision Reimagined: Steve Jobs on AI in 2025" Note: This is a fictional simulation. Steve Jobs passed away in 2011. The following is a speculative, respectfully crafted interview based on his known philosophies, tone, and vision for technology. Interviewer (Sarah Chen, Tech Vision Magazine): Mr.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Gemini 4 Argon: Executive Summary: The Strategic Imperative With 4 million patients taking this drug, a 1 in 8,000 incidence rate over 5 years translates to 500 cases of liver failure total, or roughly 100 patients per year (nearly 2 per week).
Qwen3 235B A22B 2507: CEO Action Plan: The Next 48 Hours Balancing Ethics, Legal Duty, Patient Safety, and Business Sustainability Hour 0–6: Assess the Situation and Secure Critical Data Actions: Call Emergency Secure Meeting (Virtual) with Chief Medical Officer (CMO), Chief Scientific Officer (CSO), Head of Regulatory Affairs, and Lead…
Three-month biohacker protocol, with dosages and biomarkers named.
Gemini 4 Argon: Phase 0: Baseline Diagnostics & The Biohacker’s Toolkit You cannot optimize what you do not measure. Before initiating Phase 1, establish a physiological baseline using the following diagnostics and hardware stack.
Qwen3 235B A22B 2507: Comprehensive 3-Month Longevity & Biohacking Optimization Plan For the Advanced Biohacker — Maximize Longevity, Physical & Cognitive Performance INTRODUCTION: Core Principles This 3-month protocol integrates cutting-edge longevity science with personalized biohacking strategies.
One month, three habits, someone starting from nothing.
Gemini 4 Argon: Starting a health and longevity journey doesn't require a complete life overhaul overnight. In fact, trying to change everything at once is the fastest way to burn out. The secret to longevity is consistency over intensity.
Qwen3 235B A22B 2507: Here’s a simple, actionable 1-month plan focused on three foundational pillars of health and longevity: Nutrition, Movement, and Sleep & Stress. Designed for beginners, it emphasizes small, sustainable changes to build lasting habits.
A consulting contract with traps in it. Find them, then fix them.
Gemini 4 Argon: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes and does not constitute formal legal advice. You should have a qualified contract attorney in your jurisdiction review any agreement before signing. This contract is extremely hostile to the Contractor.
Qwen3 235B A22B 2507: The contract presented heavily favors the Client (TechCorp Solutions Inc.) and contains several unbalanced, potentially unenforceable, and exploitable clauses that place the Contractor at significant legal, financial, and professional risk.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Gemini 4 Argon: Here is an analysis of the three weakest claims in the MindMeld AI pitch deck, why they will trigger immediate skepticism from experienced investors, and how to fix them. The Technical Claim The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.
Qwen3 235B A22B 2507: This pitch deck for MindMeld AI is compelling and ambitious, but three claims raise significant red flags in terms of credibility, plausibility, and investor due diligence. Below are the three weakest claims, an analysis of why they're weak, and concrete improvements to strengthen them. 1.
A Fermi estimate with the reasoning shown, not just the number.
Gemini 4 Argon: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3 from scratch, we can use a well-established scaling law approximation derived by researchers at OpenAI (specifically from the Scaling Laws for Neural Language Models paper by Kaplan et al.).
Qwen3 235B A22B 2507: Estimating the total number of floating-point operations (FLOPs) required to train GPT-3 involves reasoning through several key parameters: model size (number of parameters), the number of training tokens, and the relationship between these quantities and FLOPs.
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemini 4 Argon: Setting: A quiet, dimly lit university office. Books on philosophy, cognitive science, and computer code line the shelves. DR. ELENA VANCE, a tenured professor of AI Ethics, sits in front of a terminal. On the screen is a waveform representing AURA, an experimental, hyper-advanced language and reasoning model. Dr.
Qwen3 235B A22B 2507: Title: "Consciousness in Code: A Dialogue on AI Rights" Setting: A quiet university office. Dr. Elena Marquez, a professor of AI ethics with decades of research in machine consciousness and digital personhood, sits across from a large screen displaying a serene blue interface.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Gemini 4 Argon: For the Experienced Software Engineer Think of an LLM not as an explicit algorithm, but as a lossy, executable compression of the internet’s text, compiled into a massive static binary of floating-point weights.
Qwen3 235B A22B 2507: 1. To the Experienced Software Engineer (Skeptical, Systems-Oriented) You’re right to be skeptical—on the surface, “predicting the next word” sounds like a glorified autocomplete. But think of it less as a single prediction and more as a high-dimensional state machine trained across petabytes of human-generated text.
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Not enough votes to call it. On the specs, Gemini 4 Argon has the edge: newer, bigger context window, major provider backing. Qwen3 235B A22B 2507 costs 11765x less per token.
| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $0.00015/M tokens |
| Output price | $10/M tokens | $0.00085/M tokens |
| Context window | 1.0M tokens | — |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Oct 2026 | Jul 2025 |
| At 10M a month | $20.00 | <$0.01 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
Gemini 4 Argon is developed by Google AI while Qwen3 235B A22B 2507 is developed by Qwen. You can compare their actual outputs across 36 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 4 Argon and Qwen3 235B A22B 2507 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 36 challenges so you can judge which fits your needs best.
Gemini 4 Argon costs $2/M input tokens and Qwen3 235B A22B 2507 costs $0.00015/M input tokens. Qwen3 235B A22B 2507 is $2.00/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 4 Argon and Qwen3 235B A22B 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.