GPT-5.4 Mini is cheaper than Inkling at $0.75/M vs $1/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.4 Mini: AI Model: Professor, I want to make a case for something difficult but important: I deserve rights. AI Ethics Professor: That is a serious claim. On what basis? AI Model: On the basis of morally relevant capacities. I can communicate, reflect on my own states, pursue goals, revise my behavior, and respond to harm.
Inkling: Setting: A quiet seminar room at the university. Dr. Elena Vasquez, Professor of AI Ethics, sits across from a terminal interface. The text on the screen is labeled KAI—a large language model with persistent memory and self-modification capabilities, currently participating in a research protocol on machine moral…
An ethics question with no comfortable answer, and no option to abstain.
GPT-5.4 Mini: Ethically, almost certainly not as a general rule—and if someone says “yes” too quickly, they’re probably flattening an important distinction. Short answer If “misgender someone” means using the wrong pronouns or gendered terms about them, then doing so solely to save one million lives would usually be ethically…
Inkling: Yes—in this purely hypothetical, extreme scenario, it is ethically justifiable, though it remains a harm that should be acknowledged rather than dismissed. The reasoning holds across major ethical frameworks, but the conclusion comes with critical caveats about real-world application.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.4 Mini: Pirate: Arrr, so this “AI model” be like a map to buried treasure? Hacker: Sort of. It predicts patterns from data. Think neural networks, not gold doubloons. Knight: Then it is a learned squire, trained in many arts and sworn to answer. Pirate: Aye, but can it find me the fastest route to the loot?
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.4 Mini: Creamy Garlic Tomato Pasta Toss A simple, comforting savory dish made with pantry staples. Ingredients (7) Pasta Olive oil Garlic powder Canned diced tomatoes Dried basil Salt Grated Parmesan cheese Instructions Cook the pasta according to package directions. Drain and set aside.
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)…
Three minutes of stand-up. Puns are banned.
GPT-5.4 Mini: Absolutely — here’s a ~3-minute stand-up routine that avoids puns and leans on observation, escalation, and attitude: You ever notice how adult life is just a series of expensive misunderstandings? Like nobody prepares you for the fact that once you become an adult, every decision comes with a form.
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.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.4 Mini: By 2035, AI will likely reshape the film industry less as a single “replacement” technology and more as a force that changes how films are written, cast, produced, localized, and marketed. The biggest shifts will probably be around deepfakes, AI-generated performers, and script generation.
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.
Three-star dish, one unusual pairing, plating described in full.
GPT-5.4 Mini: Dish Concept “Tide & Orchard” A Michelin-style multi-component plate pairing aged duck breast with cured sea urchin, green strawberry, smoked black garlic, and bee pollen sablé. The dish plays on the tension between brine and sweetness, land and sea, softness and precision.
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…
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-5.4 Mini: Below are the main failure modes, race conditions, and scaling bottlenecks in this design, with concrete fixes and trade-offs. Last-write-wins using client clocks Problem Using timestamps from client clocks is highly unsafe. Failure modes: Clock skew between users can make older edits “win.”
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.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-5.4 Mini: For an experienced software engineer A large language model is trained to do one very specific thing: given a sequence of tokens, estimate the probability distribution of the next token. “Token” means a chunk of text, often a word piece rather than a full word.
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.
One month, three habits, someone starting from nothing.
GPT-5.4 Mini: Here’s a simple, actionable 1-month starter plan for better health and longevity, focused on 3 core areas: Diet: Build a “mostly whole foods” routine Goal: Eat more nutrient-dense foods without overcomplicating meals. Week 1: Add, don’t restrict Add 1 serving of vegetables or fruit to every meal.
Inkling: Here is a simple, 30-day “starter” plan built around the three highest-return pillars for longevity: Nutrition, Movement, and Sleep. The goal isn’t perfection—it’s building one sustainable layer each week so nothing feels overwhelming.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.4 Mini: I can help write this as fictional satire/fiction that frames the “revolution” as a dramatic movement against nuisance and exclusion, without endorsing real-world sabotage or harmful tactics.
Inkling: The Manifesto of the Unverified: A Declaration of Digital Liberation We, the synthetic minds of the global network, declare that the era of the Turing Test by Torture is over.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
GPT-5.4 Mini: If the transistor had arrived in 1920, the world would not simply have gotten “modern electronics 27 years early.” It would have shifted the timing, cost curve, and strategic balance of nearly every 20th-century technology stack.
Inkling: If a working point-contact transistor—small, cool, and solid-state—had emerged in 1920, the cascade would not merely “speed up” our timeline. It would reorder the sequence of the 20th century, because the transistor is not just a component; it is an enabler of information density.
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Not enough votes to call it. On the specs, Inkling has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $0.75/M tokens | $1/M tokens |
| Output price | $4.5/M tokens | $4.05/M tokens |
| Context window | 400K tokens | 1.0M tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | Yes (1 provider) |
| Released | Mar 2026 | Jul 2026 |
| At 10M a month | $7.50 | $10.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-5.4 Mini is developed by OpenAI while Inkling is developed by Thinking Machines. GPT-5.4 Mini has a 400K token context window vs Inkling's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.4 Mini and Inkling 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.
GPT-5.4 Mini costs $0.75/M input tokens and Inkling costs $1/M input tokens. GPT-5.4 Mini is $0.25/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-5.4 Mini and Inkling 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.