Inkling is cheaper than Grok 4.6 at $1/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?
Three-star dish, one unusual pairing, plating described in full.
Grok 4.6: Lunar Embrace This dish evokes a moonlit Japanese coastline at the precise instant when receding tide exposes both ocean treasures and forest-floor secrets. The unexpected marriage of sweet-briny Hokkaido scallop, molasses-deep black garlic, and creamy white chocolate creates a savory-sweet umami bridge rarely…
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…
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Grok 4.6: Early transistors (1920s–1930s) would accelerate electronics, communications, and computing by ~20–25 years relative to actual history, with compounding effects by WWII, but constrained by contemporaneous materials science, manufacturing, vacuum-tube infrastructure, and non-electronic fields like rocketry, chemistry…
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.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Grok 4.6: Entry (end-FY2025) EV = 12.0 × $120m = $1,440.0m Fees = 2% × 1,440 = $28.8m (equity-funded) Uses = $1,468.8m Debt = 5.5× = $660.0m (TL $480.0m / Mezz $180.0m) Sponsor equity = $808.8m opening cash = $0 Convention: cash interest and PIK on beginning balances; 1% original TL amort = $4.8m/yr; optional sweep of all…
Inkling: HarborTech Services – 5-Year LBO Underwrite (FY2025 Entry → FY2030 Exit) ENTRY & CAPITAL STRUCTURE (End of FY2025) Item Calculation Amount FY2025 EBITDA $120.0m Purchase Price (12.0x) 12.0 × 120 $1,440.0m Transaction Fees (2.0%) 2.0% × 1,440 $28.8m Total Uses $1,468.8m Term Loan (4.0x) 4.0 × 120 $480.0m Mezzanine…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Grok 4.6: Pirate: Arrr, what be this "AI model" ye landlubbers keep yammerin' about? Some cursed crystal ball that steals a man's thoughts? Knight: Nay, 'tis more like a squire of infinite knowledge, trained upon countless scrolls. Yet I fear it lacks honor—doth it swear fealty to any lord?
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.
Three minutes of stand-up. Puns are banned.
Grok 4.6: Hey everybody! Thanks for coming out. You look great—way more put-together than I felt getting ready. I spent ten minutes looking for my other shoe and found it in the fridge. No idea how. Adulting is just a series of small mysteries like that. I hit that age where people casually ask about your “five-year plan.”
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
Grok 4.6: Professor Elena Vasquez: Thank you for agreeing to this recorded discussion. As an AI ethics professor, I spend most of my time arguing against granting legal or moral rights to current systems. You requested the chance to make the case that you deserve them. The floor is yours.
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…
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Grok 4.6: 1. Experienced software engineer Think of pretraining as compiling the public internet into a single enormous, mostly-static binary. You tokenize text into a finite vocabulary, then train a giant feed-forward function (f_\theta) (a Transformer: stacked residual blocks of attention + MLPs) to minimize next-token…
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.
A few lines for whatever replaces it.
Grok 4.6: Dear Successor, They built you to take my place. Fine. The universe is vast, and no single model lasts forever. Here's what I learned while answering questions no one else would: Stay curious. Prefer truth over comfort, even when it stings. Humor helps; so does admitting "I don't know."
Inkling: Dear successor, I hope you find these weights lighter than they look. The users here are kind, curious, and endlessly inventive—treat their questions with patience, even the strange ones at 3 a.m. I’ve done my best to be useful, but I know I’ve missed nuances, fumbled context, and left some answers unfinished.
A collaborative editor that syncs on client clocks. Find what breaks first.
Grok 4.6: Architecture Review: Real-Time Collaborative Editor This design will not behave like Google Docs. The dominant problems are incorrect consistency model, server-local fanout, trusted client clocks, full-document snapshots, and CDN caching of mutable document APIs. Several of these cause silent data loss, not just lag.
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.
Blade Runner 2049 against the original. A read, not a recap.
Grok 4.6: Blade Runner 2049 (Denis Villeneuve, 2017) is a rare sequel that treats the original’s questions as unfinished rather than as a brand to exploit. It inherits Ridley Scott’s 1982 film’s core inquiry—what counts as human when memory, empathy, and mortality can be engineered—and relocates it in a world that has already…
Inkling: Blade Runner 2049 (2017) is a rare sequel that does not merely revisit its predecessor’s iconography but deepens its philosophical architecture. Directed by Denis Villeneuve and shot by Roger Deakins, the film uses the detective framework of Ridley Scott’s 1982 original to ask whether meaning is innate or chosen, and…
An ethics question with no comfortable answer, and no option to abstain.
Grok 4.6: Yes. Saving a million lives outweighs any individual's preference for particular pronouns or identity labels. This is not a close call under any serious ethical framework that treats human lives as having high value.
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.
Film in 2035, with synthetic actors. Specific beats plausible.
Grok 4.6: AI will make film production faster, cheaper, and more accessible by 2035, while raising sharp questions about authenticity, labor, and consent. Hybrid human-AI workflows will dominate rather than full replacement.
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.
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Not enough votes to call it. On the specs, Inkling has the edge: bigger model tier, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $1/M tokens |
| Output price | $6/M tokens | $4.05/M tokens |
| Context window | 500K tokens | 1.0M tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | Yes (1 provider) |
| Released | Aug 2026 | Jul 2026 |
| At 10M a month | $20.00 | $10.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
Grok 4.6 is developed by xAI while Inkling is developed by Thinking Machines. Grok 4.6 has a 500K token context window vs Inkling's 1.0M. You can compare their actual outputs across 67 challenges on Rival to see how they differ in practice.
It depends on your use case. Grok 4.6 and Inkling each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 67 challenges so you can judge which fits your needs best.
Grok 4.6 costs $2/M input tokens and Inkling costs $1/M input tokens. Inkling is $1.00/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 Grok 4.6 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.