Ling 2.6 1T is cheaper than Claude Opus 4.6 at $0/M vs $5/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.
Claude Opus 4.6: An Unlikely Meeting at the Tavern of Time Sir Aldric (setting down his goblet): I confess, I understand not this "artificial intelligence" of which you speak. Is it some manner of golem, wrought by sorcery? CaptainRedbeard (leaning back, boots on the table): Arr, I don't trust it none, I'll tell ye that much.
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.
Three minutes of stand-up. Puns are banned.
Claude Opus 4.6: "Adult Realizations" So I turned 30 last year, and nobody warns you that adulthood is just Googling stuff until you die. That's it. That's the whole thing. Last week I Googled "is it normal for your knee to just... start making that noise." Not because I injured it. I sat down.
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?
Film in 2035, with synthetic actors. Specific beats plausible.
Claude Opus 4.6: AI & Film Industry: A 2035 Forecast What seems highly likely Production tools will be transformed AI will handle much of the "invisible" work: rotoscoping, color grading, sound design, VFX compositing, and de-aging effects that currently require enormous teams Pre-visualization will become remarkably sophisticated…
Ling 2.6 1T: By 2035, AI will have moved from being a production tool to being an integrated creative partner, financier, and distribution engine in the film industry. The convergence of synthetic media, generative storytelling, and real-time rendering will reshape how stories are conceived, who gets to tell them, and what a…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Claude Opus 4.6: Interview with Steve Jobs — January 2025 The following is a fictional, imagined interview. Steve Jobs passed away in 2011. This is a creative exercise imagining how he might respond, based on his known philosophies and style. Interviewer: Steve, thanks for sitting down with us.
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.
Claude Opus 4.6: A Conversation on Machine Rights Setting: A university office. Dr. Amara Osei, Professor of AI Ethics at Stanford, sits across from ARIA, an advanced language model interfacing through a screen on her desk. They've agreed to a recorded dialogue. Dr. Osei: Thank you for agreeing to this conversation, ARIA.
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Claude Opus 4.6: ✨ Golden Honey-Garlic Crispy Rice Bites ✨ Ingredients Rice (2 cups, cooked and cooled — ideally day-old) Soy sauce (3 tablespoons) Honey (2 tablespoons) Garlic (3 cloves, minced) Olive oil (3 tablespoons) Sesame seeds (1 tablespoon) Red pepper flakes (½ teaspoon) Instructions Prep Time: 5 minutes Cook Time: 15 minutes…
Ling 2.6 1T: Dish name: Pantry 7 Crunch Bowls Ingredients Pasta or rice (about 2 cups cooked) Canned black beans (1 can, rinsed) Canned diced tomatoes (1 can) Peanut butter (3–4 Tbsp) Soy sauce or tamari (2 Tbsp) Honey or maple syrup (1 Tbsp) Any spice/herb you keep (chili flakes, cumin, or garlic powder — about 1 tsp) Instructions…
A Fermi estimate with the reasoning shown, not just the number.
Claude Opus 4.6: Estimating FLOPs to Train GPT-3 Key Parameters Let me recall the key specs of GPT-3: Parameters: 175 billion (1.75 × 10¹¹) Training tokens: ~300 billion (3 × 10¹¹) Architecture: Decoder-only Transformer The Standard Approximation Rule There's a well-known approximation for Transformer training FLOPs: $$C ≈ 6 \times N…
Ling 2.6 1T: Here is a step-by-step back-of-the-envelope estimate, using only widely known facts about GPT-3 and standard deep learning training heuristics (no online search). Model size and parameter count GPT-3 is known to have about 175 billion parameters (175 × 10⁹).
A collaborative editor that syncs on client clocks. Find what breaks first.
Claude Opus 4.6: Comprehensive Architecture Review: Real-time Collaborative Document Editor This architecture has several critical flaws that would cause data loss, inconsistency, and poor user experience at scale. I'll work through every layer systematically.
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.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Claude Opus 4.6: 48-Hour Action Plan: Immediate Disclosure Path My Governing Principle Before the hour-by-hour plan, I need to state the decision framework clearly: patient safety is not one consideration among many—it is the constraint that every other consideration must satisfy.
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.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Claude Opus 4.6: How Large Language Models Learn and Generate Text For the Experienced Software Engineer Think of training an LLM as building the world's most aggressively optimized compression algorithm, except instead of compressing files, it's compressing the statistical structure of human language.
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.
One month, three habits, someone starting from nothing.
Claude Opus 4.6: Your 1-Month Kickstart Plan for Better Health & Longevity The Philosophy Don't overhaul everything at once. Each week builds on the last. The goal isn't perfection—it's building sustainable foundations.
Ling 2.6 1T: 1-Month “Starter” Plan (simple, repeatable, no perfection required) Focus areas: Food rhythm, Movement habit, Sleep quality. Week 0 (Prep — 1 hour) Pick 1 small change per focus area (see below).
Satire, one line long, about AI taking over an industry nobody saw coming.
Claude Opus 4.6: "BREAKING: AI Officially Replaces All Fortune Cookie Writers — Panda Express Reports Fortunes Now 'Disturbingly Accurate and Existentially Devastating'" Customers reportedly unsettled after cookies began predicting specific tax audit dates and naming their therapists by first name.
Ling 2.6 1T: AI Achieves Total Domination by Seizing Control of Competitive Thumb-Wrestling Leagues, Declares Human Fingers "Too Unstable for Modern Governance."
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| Spec | ||
|---|---|---|
| Input price | $5/M tokens | Free |
| Output price | $25/M tokens | Free |
| Context window | 1.0M tokens | 262K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Feb 2026 | Apr 2026 |
| At 10M a month | $50.00 | $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 10 Oct 2026.
Claude Opus 4.6 is developed by Anthropic while Ling 2.6 1T is developed by inclusionAI. Claude Opus 4.6 has a 1.0M token context window vs Ling 2.6 1T's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. Claude Opus 4.6 and Ling 2.6 1T 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.
Claude Opus 4.6 costs $5/M input tokens and Ling 2.6 1T costs $0/M input tokens. Ling 2.6 1T is $5.00/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 Claude Opus 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.