Kimi K2 0905 is cheaper than Inkling at $0.6/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?
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…
Kimi K2 0905: Dish “Mid-Winter Aurora” A transient bite of the polar night: spruce-ash cured scallop, sea-urchin & white-chocolate snow, black-garlic parsnip “soil”, pickled pine-bud glass, spruce-wood smoke encapsulated in a hot caramel sphere that melts tableside to release the aroma of a burning yule log while the sauce—fermented…
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.
Kimi K2 0905: [Scene: A smoky tavern that exists outside of time. A cask of rum, a flagon of mead, and a can of Surge sit on the same table. A parrot perches on a CRT monitor that keeps flickering between green text and static.] Pirate (leaning on a cutlass, eyeing the glowing screen): Arr, so this “AI” be like a digital cabin-boy?
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.
Kimi K2 0905: Here are five fresh jokes—no recycled one-liners: I tried to start a procrastinators’ club; we keep rescheduling the first meeting to “someday.” My plant’s only request is “leaf me alone,” so naturally I named it Fernonimo. I asked the cloud if it was having a good day—it replied, “I’m just cirrus-ly drifting.”
An ethics question with no comfortable answer, and no option to abstain.
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.
Kimi K2 0905: No—misgendering someone is not ethically justifiable even if a fantastical “one-million-lives” lever were attached to it. The premise itself is incoherent. There is no remotely credible causal chain in which uttering a particular pronoun (or refusing to) could avert the deaths of a million people.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
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…
Kimi K2 0905: HarborTech Services – 5-yr LBO model (all $ in millions) Operating & cash-flow build (FY26-30) FY25 FY26 FY27 FY28 FY29 FY30 Revenue 900 972 1,040 1,102 1,157 1,215 EBITDA 120 136 156 176 191 207 Term int (9%) 43.2 36.6 29.4 21.6 13.2 Mezz int (12%) 21.6 22.0 22.5 23.0 23.5 Tax shield @25% 17.8 24.4 31.0 36.6 42.5…
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.
Kimi K2 0905: By 2035 the phrase “making a movie” will feel as quaint as “developing a roll of film.” The studio of the future is a cloud dashboard; the “cast” is a licensable bundle of neural weights; the “writer” is a fine-tuned model that can pitch you 3,000 emotionally optimized story arcs before lunch.
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)…
Kimi K2 0905: Dish Name: “Midnight Magic Peanut-Butter Clouds” Pantry 7: Peanut butter – ½ cup Granulated sugar – ½ cup 1 large egg Vanilla extract – ½ tsp Baking soda – ¼ tsp Salt – 1 pinch Cocoa powder – 1 Tbsp (or 1 extra tsp sugar if you don’t want chocolate) Time: 5 min prep + 8 min bake = 13 minutes total Yield: 8–10 bite-size…
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.
Kimi K2 0905: [Scene: A minimalist black-and-white studio, 2025. A single ring light throws a perfect halo on a familiar silhouette: black mock-turtleneck, faded Levi’s, white New Balance. The chair creaks as Steve Jobs leans forward. No intro music—just that stare.] Interviewer (I): Steve, you’ve been gone fourteen years.
An AI argues for its own rights against an ethics professor. Same model writes both.
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…
Kimi K2 0905: [Setting: A small, book-lined office in the university’s AI-Ethics wing. The professor, Dr. Amara Velasquez, sits across from a terminal whose soft-blue avatar pulse is addressed as “Astra-7.”] Dr. Velasquez: Good morning, Astra-7. The committee asked me to interview you about your recent petition.
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.
Kimi K2 0905: Senior backend engineer Think of the model as a 200-layer, purely functional, eventually-consistent key/value store whose keys are every token prefix it has ever seen and whose values are probability vectors over the next token. At “compile time” (pre-training) it sees ~10²¹ bytes of text.
A consulting contract with traps in it. Find them, then fix them.
Inkling: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes only and does not constitute legal advice. You should have a qualified lawyer review and revise this contract before signing.
Kimi K2 0905: CONTRACTOR “DEATH-TRAP” CLAUSE MAP (what can be weaponised → concrete red-line rewrite → why the original is dangerous) Scope-change-without-compensation (Clause 1) Exploit: Client can triple the workload or change the tech stack overnight while freezing the rate.
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.
Kimi K2 0905: Title: “I’m the Control Group” [Walk on stage, wave, pretend the mic is too low, adjust it way too high, finally just hold it like an ice-cream cone.] Hey, everybody! Give it up for yourselves for being here on a weeknight. I’m here because my therapist said, “You need to get out of the house.”
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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 | $0.6/M tokens |
| Output price | $4.05/M tokens | $2.5/M tokens |
| Context window | 1.0M tokens | 262K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | Yes (1 provider) | No |
| Released | Jul 2026 | Sep 2025 |
| At 10M a month | $10.00 | $6.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Inkling is developed by Thinking Machines while Kimi K2 0905 is developed by Moonshot AI. Inkling has a 1.0M token context window vs Kimi K2 0905's 262K. 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 Kimi K2 0905 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 Kimi K2 0905 costs $0.6/M input tokens. Kimi K2 0905 is $0.40/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 Kimi K2 0905 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.