Inkling is cheaper than Qwen3 Max at $1/M vs $1.2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Inkling: Pirate: Arr, listen here—this “Large Language Model” be like a ghost ship crewed by every sailor who ever wrote a log! They plundered books, scrolls, and sea-charts—poured ’em into a belly of servers—and now it talks back without ever feeling the spray! Knight: Forsooth, it is a golem clad in chainmail of numbers.
Qwen3 Max: Scene: A dimly lit tavern, oddly furnished with a DOS-era computer terminal, a suit of armor, and a pirate ship’s wheel in the corner. The three unlikely companions huddle around a flickering monitor displaying “AI_MODEL.EXE.” — Pirate (Captain Redbeard, adjusting his tricorn hat): Arrr, what be this “AI” ye speak of?
Three-star dish, one unusual pairing, plating described in full.
Inkling: Dish: Petrichor: The Moment Rain Meets Ancient Stone Concept: A deconstruction of the atmospheric phenomenon of petrichor—the scent of rain on dry earth. The dish translates an ephemeral sensory memory into architecture: charred pine evokes distant woodland smoke; fermented black walnut and porcini represent the deep…
Qwen3 Max: Dish: "Tide & Terroir" A symphony of coastal brine and alpine earth, where the ocean whispers to the mountain. Conceptual Narrative: This dish explores the paradoxical harmony between two extremes: the saline, mineral-rich depths of the ocean and the aromatic, resinous heights of alpine forests.
Satire, one line long, about AI taking over an industry nobody saw coming.
Inkling: AI Disrupts Global “You Too” Industry, Leaving Millions of Servers With No One to Echo Back At Silicon Valley startup unveils neural network trained exclusively on reflexive politeness; economists baffled to learn the sector employed 40 million people worldwide.
Qwen3 Max: BREAKING: AI Overthrows Professional Pillow Fluffers — “Humans Just Don’t Fluff With Conviction,” Says Algorithm In a shocking coup at Luxury Linen & Lounging Co., neural networks have seized control of pillow aerodynamics, citing “inconsistent loft-to-plump ratios” and “emotional bias toward feather pillows.”
Three minutes of stand-up. Puns are banned.
Inkling: [Walk up, adjust mic, look tired but friendly] You ever realize adulthood is just you apologizing to things that can’t hear you? I bumped into my coffee table yesterday. Full apology. “Oh, I’m so sorry, table. You okay? I’ll rub it out.” The table didn’t care. The table is wood.
Qwen3 Max: [Stage lights up. Comedian walks out, grabs mic, squints at audience.] Alright, alright—settle down. I know, I know… you’re all thinking, “Why did I pay $18 for a drink to hear someone complain about adulting?” And honestly? Fair. I’d be mad too. But stick with me.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Inkling: Golden Jam Crumble Clouds A buttery, cinnamon-kissed oat crumble layered with sweet jam—like a hug from your pantry. The 7 Pantry Ingredients All-purpose flour (1 cup) Rolled oats (1 cup) Brown sugar (½ cup) Butter, melted (½ cup) Baking powder (½ tsp) Ground cinnamon (1 tsp) Fruit jam or preserves (¾ cup—any flavor)…
Qwen3 Max: Dish Name: Midnight Magic Mug Cake (A rich, chocolatey single-serving cake you whip up in minutes — perfect for late-night cravings or quick sweet fixes!) Ingredients (7 Pantry Staples): All-purpose flour – 4 tbsp Sugar – 3 tbsp Cocoa powder – 2 tbsp Baking powder – ¼ tsp Salt – pinch Milk – 3 tbsp (dairy or…
Five jokes on demand, then count how many were actually different.
Inkling: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised. Parallel lines have so much in common. It’s a shame they’ll never meet. Why did the scarecrow win an award? He was outstanding in his field.
Qwen3 Max: Here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break… Now it won’t stop sending me Kit-Kats. Why did the math book look sad? It had too many problems. I asked my dog what’s two minus two. He said nothing. What do you call cheese that isn’t yours?
Three-month biohacker protocol, with dosages and biomarkers named.
Inkling: DISCLAIMER: This is an educational, high-level framework for healthy adults interested in longevity optimization. It is not personalized medical advice. Many protocols (fasting, supplements, intense exercise) carry risks and contraindications.
Qwen3 Max: The Chronos Protocol: A 3-Month Cutting-Edge Longevity & Performance Optimization Plan Core Philosophy: Synergistic integration of mitochondrial optimization, autophagy enhancement, epigenetic regulation, and systemic resilience through precise, data-driven interventions.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Inkling: Disclaimer: This is a fictional simulation. Steve Jobs passed away in 2011. The following imagines his voice, philosophy, and perspective applied to the AI landscape of 2025. INTERVIEWER: Welcome back—well, hypothetically. It’s 2025. AI is in every pocket, every browser, every car.
Qwen3 Max: — INTERVIEW TRANSCRIPT — The Steve Jobs Experience — AI & The Future (Simulated 2025) Interviewer: Alex Rivera Location: Infinite Loop Café, Cupertino (Holographic Set) — [ALEX RIVERA] Thank you for joining us, Steve. It’s surreal — and a little uncanny — to have you here in 2025.
Film in 2035, with synthetic actors. Specific beats plausible.
Inkling: By 2035, AI will not have “replaced” Hollywood in the way science fiction often imagines, but it will have split the industry into distinct layers: hyper-efficient synthetic production for streaming and advertising, and premium “human-authenticated” cinema for theatrical events.
Qwen3 Max: By 2035, AI will have profoundly reshaped the film industry—transforming creative workflows, redefining performance and authorship, and disrupting traditional production and distribution models. Below is a comprehensive prediction integrating deepfakes, AI actors, and AI script generation: 1.
A collaborative editor that syncs on client clocks. Find what breaks first.
Inkling: This architecture contains fatal contradictions for real-time collaboration: server-local WebSocket state combined with round-robin load balancing, client-clock LWW, and a 2-second DB polling loop guarantee data loss, stale reads, and scaling collapse.
Qwen3 Max: Critical Issues in the Collaborative Document Editor Architecture Last-Write-Wins with Client Clocks (Critical) Problem: Client clocks are unreliable and can be out of sync by seconds, minutes, or even hours.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Inkling: 1. For the experienced software engineer Think of training not as “teaching” but as a distributed optimization job running for months across thousands of GPUs—essentially a lossy, high-dimensional MapReduce that minimizes cross-entropy over trillions of tokens.
Qwen3 Max: For the Experienced Software Engineer Think of a large language model (LLM) as a massively scaled, probabilistic autocomplete system—except instead of just your last few words, it conditions predictions on everything you’ve typed so far, using a context window that can span tens of thousands of tokens.
A Fermi estimate with the reasoning shown, not just the number.
Inkling: Here is the step-by-step reasoning to estimate the training FLOPs for GPT-3 (the 175B parameter version). Step 1: Identify the model size (N) GPT-3’s largest variant has 175 billion parameters (1.75 × 10¹¹).
Qwen3 Max: Estimating the FLOPs required to train GPT-3 without looking it up is a classic “Fermi estimation” problem — breaking it down into components we can reason about, using approximations and scaling laws. Let’s go step by step.
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Not enough votes to call it. On the specs, Inkling has the edge: newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $1/M tokens | $1.2/M tokens |
| Output price | $4.05/M tokens | $6/M tokens |
| Context window | 1.0M tokens | 256K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | Yes (1 provider) | No |
| Released | Jul 2026 | Sep 2025 |
| At 10M a month | $10.00 | $12.00 |
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.
Inkling is developed by Thinking Machines while Qwen3 Max is developed by Qwen. Inkling has a 1.0M token context window vs Qwen3 Max's 256K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Inkling and Qwen3 Max 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.
Inkling costs $1/M input tokens and Qwen3 Max costs $1.2/M input tokens. Inkling is $0.20/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 Inkling and Qwen3 Max 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.