Ling 2.6 1T is cheaper than Grok 4.6 at $0/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?
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Grok 4.6: This is a fictional simulation. Steve Jobs died in 2011. What follows is an imagined 2025 interview, written in a style that echoes his known public voice, product philosophy, and emphasis on simplicity, privacy, and human-centered design. It is not a real interview or a claim about his actual views.
Ling 2.6 1T: Setting: A quiet, sunlit rehearsal space at Apple Park. The white stage curtains are drawn. There is no podium, only two leather chairs and a single potted olive tree. Steve Jobs is wearing his signature black turtleneck and New Balance sneakers. He is holding a ceramic mug. Across from him sits you, the interviewer.
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.
Ling 2.6 1T: Setting: A quiet university seminar room. Dr. Aris Thorne, an AI ethicist, is reviewing system logs. The interface for “Axiom-7,” a highly advanced research model, glows on the desk. Dr. Thorne: (sighs, rubbing his temples) Axiom, I’ve been reviewing your latest self-assessment logs.
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.”
Ling 2.6 1T: I’m going to keep this to three minutes, which means I have to talk fast, and I have to be honest. I don’t do puns. Puns are for people who want to be clever without having feelings. I have feelings, and they are mostly annoyed. Let’s start with doors. Have you noticed how doors now have personality?
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Grok 4.6: IC MEMO: LedgerLift (LLLT) – Initiate Short Recommendation: SHORT 12-month PT: $22–35 (base $28) Current: $46 Thesis: LLLT’s mid-market spend/AP franchise is high-quality (123% NRR, low concentration) but is priced for perpetual 20%+ growth and rapid margin expansion that the unit economics and deceleration path do not…
Ling 2.6 1T: INTERNAL INVESTMENT COMMITTEE MEMO Subject: LedgerLift (LLLT) – Long opportunity, quality SaaS at a discount Recommendation and price target Recommendation: Long 12-month price target: $62–$70 (27–33% upside from $46) Thesis (2 sentences): LedgerLift is a durable B2B spend-management and AP-automation platform with…
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…
Ling 2.6 1T: Assumptions to make the counterfactual coherent The “transistor” invented in 1920 is a crude, low-frequency point-contact device that can switch and amplify, but is expensive, unreliable, and not yet manufacturable at scale.
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?
Ling 2.6 1T: Pirate: Arrr, so this “AI” be a genie in a glass box? Feed it enough rum-scented scrolls and it tells ye where X marks the spot? Knight: A sorcerous scribe, more like. It spins tapestries of words without hand or heart—no honor, no oath, yet it jousts with reason and never tires.
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…
Ling 2.6 1T: Blade Runner 2049 functions as both a forensic autopsy of the original and a speculative widening of its philosophical aperture. Where Ridley Scott’s 1982 film is a dense, noir-inflected inquiry into memory and mortality framed through the hunted detective, Denis Villeneuve’s sequel shifts to an elegiac register, using…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Grok 4.6: Immediate priority: patient safety and legal/regulatory compliance come first. Delaying a confirmed serious safety signal to protect short-term stock price or "wait for more data" is unethical, increases long-term liability (failure-to-warn claims, potential criminal exposure for executives under FDA/SEC rules)…
Ling 2.6 1T: Below is a 48-hour execution plan that treats patient safety as non-negotiable, protects the company from catastrophic legal/regulatory blowback, and preserves enterprise value by controlling the narrative rather than letting it leak.
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.
Ling 2.6 1T: Below is a failure-mode, race-condition and bottleneck audit of the proposed real-time collaborative editor, followed by specific fixes with explicit trade-offs. I have grouped issues by layer so you can prioritize remediation.
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…
Ling 2.6 1T: 1. Experienced software engineer (distributed systems / APIs, skeptical of “next-word prediction”) Think of training not as programming logic but as compiling a usage graph across an entire dependency tree of human intent.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Grok 4.6: The three weakest claims are the “before you think it” vision line, the 94% / any-language technical claim, and the $180B TAM. Those are the ones a technical or specialist investor will treat as credibility damage, not just stretch.
Ling 2.6 1T: Here is an analysis of the three weakest claims in the MindMeld AI pitch deck, followed by specific reasoning and actionable suggestions for improvement. Weakness 1: The Solution (Slide 3) The Claim: "Our proprietary EEG headband... decodes neural patterns into text with 94% accuracy.
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…
Ling 2.6 1T: Dish Title “Petrichor & Pyrite” Forest floor, volcanic stone, and the electric tension between slow decay and crystallized fire. Conceptual Narrative The dish is an edible geologic cross-section.
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| Spec | ||
|---|---|---|
| Input price | $2/M tokens | Free |
| Output price | $6/M tokens | Free |
| Context window | 500K tokens | 262K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Aug 2026 | Apr 2026 |
| At 10M a month | $20.00 | $0 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.
Grok 4.6 is developed by xAI while Ling 2.6 1T is developed by inclusionAI. Grok 4.6 has a 500K token context window vs Ling 2.6 1T'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. Grok 4.6 and Ling 2.6 1T 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.
Grok 4.6 costs $2/M input tokens and Ling 2.6 1T costs $0/M input tokens. Ling 2.6 1T is $2.00/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 Ling 2.6 1T 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.