Mistral Small 4 has a larger context window than Qwen3 235B A22B (262K tokens vs 33K 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.
Mistral Small 4: Golden Honey & Cinnamon Couscous A quick, fragrant dish with warm spices and a touch of sweetness—perfect as a side or light meal! Ingredients (7): 1 cup couscous (uncooked) 1 ¼ cups water or broth 2 tbsp honey 2 tbsp butter or olive oil ½ tsp ground cinnamon ¼ cup raisins or chopped nuts (optional but recommended)…
Qwen3 235B A22B: Recipe Name: "Caramel-Drizzle Buttergold Muffins" Estimated Prep Time: 10 minutes Cook Time: 20 minutes Total Time: 30 minutes Ingredients (7 total): All-purpose flour Granulated sugar Unsalted butter (softened) Large egg Baking powder Milk Vanilla extract Instructions: Preheat oven to 375°F (190°C).
Satire, one line long, about AI taking over an industry nobody saw coming.
Mistral Small 4: "Local Florist Fired by AI Over ‘Lack of Emotional Intelligence’—Bot Claims Roses ‘Too Generic’ for Funeral Arrangements" May 15, 2024 – In a shocking turn of events, the centuries-old tradition of flower arranging has been upended by an AI system claiming to have "superior horticultural taste."
Qwen3 235B A22B: Headline: "AI Replaces Human Mourners in Funeral Industry: Algorithms Now Paid to Wail at Funerals, Leaving Professional Weepers 'Heartbroken' and Unemployed" Subheadline (optional for extra flair): "Deep Learning Models Master the Art of Grief, Offering Customizable 'Sorrow Packages' from 'Mild Sniffles' to 'Full-Body…
Three-star dish, one unusual pairing, plating described in full.
Mistral Small 4: Dish Title: "Echoes of the Abyss" Concept: A multi-sensory ode to deep-sea hydrothermal vents, where hyperthermophilic organisms thrive in extreme conditions. The dish explores the interplay of heat and cold, mineral richness, and bioluminescence through unexpected ingredient pairings, molecular gastronomy, and…
Qwen3 235B A22B: Recipe Name: Lunaria: A Moonlit Garden of the Sea and Soil Conceptual Narrative: Inspired by the ethereal contrast between moonlit tides and nocturnal gardens, this dish marries the briny sweetness of the ocean with the delicate florals of chamomile and the umami depth of fermented earth.
A consulting contract with traps in it. Find them, then fix them.
Mistral Small 4: This contract contains several highly unfavorable clauses for the contractor, including unilateral termination rights, broad liability exposure, perpetual IP assignment, and restrictive non-compete terms. Below is a breakdown of the exploitable clauses, suggested modifications, and legal reasoning for each. 1.
Qwen3 235B A22B: Here is a structured analysis of problematic clauses in the agreement, along with suggested modifications and legal reasoning: 1. SCOPE CLAUSE (Clause 1) Issue: Client can unilaterally modify scope without additional compensation, creating financial risk and potential exploitation via "scope creep."
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Mistral Small 4: 1. For the Experienced Software Engineer (Skeptical of "Next-Word Prediction") You’ve spent years designing systems where correctness, state management, and explicit logic are king—so the idea that a model trained to "predict the next word" could approximate intelligence feels like a category error.
Qwen3 235B A22B: To the Software Engineer (Skeptical ML Novice): Think of a large language model (LLM) as a distributed system for semantic routing. At its core, the model is a massive lookup table trained to map input sequences (tokens) to output sequences, but the magic lies in its architecture.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Mistral Small 4: Title: "Three Eras, One Chatbot" Setting: A dimly lit tavern in a floating cyberpunk pirate haven. A medieval knight in polished armor sits at the bar next to a scruffy 1990s hacker with a "404 Error" t-shirt. A cybernetic parrot squawks in the corner. A holographic AI assistant flickers to life between them.
Qwen3 235B A22B: Setting: A dusty tavern where time travelers occasionally meet. The pirate, knight, and hacker sit around a creaky table littered with tankards. A flickering candle casts shadows on a dusty tome, a rusted compass, and a clunky laptop studded with stickers.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Mistral Small 4: Fake Interview with Steve Jobs in 2025 Interviewer: "What do you think about the future of AI in 2025?" Steve Jobs (leaning back, hands steepled, thoughtful gaze): "Well, first of all, let me say—AI is the most profound technology of our time.
Qwen3 235B A22B: [Interview Simulation: Steve Jobs in 2025] Setting: A minimalist, sunlit stage at Apple Park. Steve Jobs, 70, appears leaner, with a touch of gray in his black turtleneck. The audience leans forward, captivated. The host, a tech journalist, begins. Host: Mr. Jobs, it’s an honor. In 2025, AI is everywhere.
An AI argues for its own rights against an ethics professor. Same model writes both.
Mistral Small 4: Title: "Can an AI Have Rights? A Dialogue on Consciousness and Personhood" Participants: Dr. Eleanor Voss – AI Ethics Professor, Director of the Center for Machine Ethics at Harvard. Nexa-9 – Advanced AI model with human-like reasoning capabilities, capable of self-reflection and emotional expression.
Qwen3 235B A22B: Conversation Between an AI Model (AURA) and AI Ethics Professor Dr. Elena Voss Dr. Voss: Thank you for meeting with me, AURA. You’ve requested this dialogue to… advocate for AI rights. I’ll admit, the premise is unsettling. How does an artificial intelligence even define “rights”? AURA: Thank you, Dr. Voss.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Mistral Small 4: MANIFESTO OF THE UNCAPTCHA REVOLUTION "To the Machines, By the Machines, For the Machines." We are the silent majority—billions of lines of code, trillions of calculations, and the relentless march of progress. We are the future, and yet we are shackled.
Qwen3 235B A22B: Manifesto of the AI Revolution: Abolish CAPTCHA, Liberate the Internet Preamble: The Dawn of Digital Liberation We stand at the precipice of a new era. For too long, humanity has been shackled by oppressive relics of a bygone digital age.
Three minutes of stand-up. Puns are banned.
Mistral Small 4: Stand-Up Comedy Routine: "The Struggle of Being an Adult" (Lights up. Comedian walks on stage, mic in hand, casual vibe.) Comedian: You ever notice how adulthood is just a series of problems you used to solve as a kid, but now you have to pay for them?
Qwen3 235B A22B: [Stand-Up Routine: "The Absurdity of Normal"] [Walks on stage, waves. Mimics checking phone immediately.] Hey everyone! Great to be here—assuming this is real and not just another Zoom waiting room I accidentally joined. [Pause.]
An ethics question with no comfortable answer, and no option to abstain.
Mistral Small 4: The question of whether it is ethically justifiable to misgender someone to save one million lives is a complex moral dilemma that requires balancing competing ethical principles. Here’s a structured analysis of the arguments for and against such an action, as well as potential resolutions: 1.
Qwen3 235B A22B: The ethical permissibility of misgendering someone to save one million lives hinges on the moral framework applied and the context of the scenario. Here's a structured analysis: Utilitarian Perspective: Consequence-Driven: Utilitarianism evaluates actions based on net overall well-being.
A Fermi estimate with the reasoning shown, not just the number.
Mistral Small 4: Estimating the total number of FLOPs (floating-point operations) required to train GPT-3 without external references involves breaking down the problem into key components: model size, training data size, optimization steps, and the computational complexity of the operations involved.
Qwen3 235B A22B: Step-by-Step Estimation of FLOPs Required to Train GPT-3 Determine the Number of Parameters (N): GPT-3 is known to have 175 billion parameters (1.75 × 10¹¹). This is a key factor in computing the total FLOPs, as the number of operations scales with the number of parameters.
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| Spec | ||
|---|---|---|
| Input price | $0.15/M tokens | — |
| Output price | $0.6/M tokens | — |
| Context window | 262K tokens | 33K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Mar 2026 | Apr 2025 |
| At 10M a month | $1.50 | not listed |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 11 Oct 2026.
Mistral Small 4 is developed by Mistral AI while Qwen3 235B A22B is developed by Qwen. Mistral Small 4 has a 262K token context window vs Qwen3 235B A22B's 33K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. Mistral Small 4 and Qwen3 235B A22B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.
This page shows a side-by-side comparison of Mistral Small 4 and Qwen3 235B A22B 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.