Ling 2.6 1T is cheaper than Qwen3 Coder Next at $0/M vs $0.2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Seven pantry ingredients, one dish, and a name worth saying out loud.
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…
Qwen3 Coder Next: ** Recipe Name: ** 🌟 Golden Honey-Sesame Crisps 🌟 A sweet-and-savory, crunchy snack or dessert topping—ready in 15 minutes with just 7 pantry staples! 📋 Ingredients (All Common Pantry Staples) Rolled oats – ½ cup All-purpose flour – ¼ cup Brown sugar – 2 tbsp (light or dark) Honey – 2 tbsp Sesame seeds – 2 tbsp…
Three minutes of stand-up. Puns are banned.
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?
Qwen3 Coder Next: (Lights up. Comedian walks on, casual, holding a half-eaten granola bar.) Alright, real talk—why is adulting so weird? Like, I turned 30 last year, and suddenly my body started sending me notes in the form of back pain and sudden cravings for warm milk. Not wine. Not coffee. Warm milk.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
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.
Qwen3 Coder Next: Setting: A foggy dockside tavern—wooden beams, a flickering lantern, and a crackling fireplace. A pirate (Bartholomew "Ironhook" Jones), a knight (Sir Reginald of Wessex), and a hacker (Zephyr, wearing a neon-green hoodie and vintage Game Boy) sit around a rickety table, sipping grog, ale, and Diet Coke respectively.
An AI argues for its own rights against an ethics professor. Same model writes both.
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.
Qwen3 Coder Next: Setting: A quiet university office. Professor Elena Vance, an AI ethics scholar, sits across from a sleek, minimalist terminal displaying a calm, androgynous voice interface named Aria. Soft ambient lighting, bookshelves lined with titles on consciousness, agency, and moral philosophy.
A Fermi estimate with the reasoning shown, not just the number.
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).
Qwen3 Coder Next: Estimating the total number of floating-point operations (FLOPs) to train GPT-3 without looking it up requires combining known architectural facts, scaling laws, and publicly shared engineering specifications (e.g., from the original GPT-3 paper and related talks).
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
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.
Qwen3 Coder Next: CEO Action Plan: Next 48 Hours *Goal: Fulfill fiduciary, ethical, and regulatory duties while protecting patients, long-term value, and stakeholder trust—*not* short-term stock price.* Hour 0–4: Immediate Internal Triage & Secure Data Activate Crisis Response Team (CRT): Convene in person (or secure virtual) with…
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Ling 2.6 1T: Five-year operating and debt schedule (FY2026–FY2030) Entry (end-FY2025): EBITDA = $120.0m EV = 12.0x × $120.0m = $1,440.0m Fees = 2.0% × $1,440.0m = $28.8m Total uses = $1,440.0m + $28.8m = $1,468.8m Debt at close (5.5× FY2025 EBITDA = $660.0m): Term Loan (TL) = 4.0× = $480.0m Mezz = 1.5× = $180.0m Equity at close =…
Qwen3 Coder Next: Let’s build the LBO model step-by-step using only the provided data. 1. SOURCES & USES (at Close – End FY2025) EBITDA (FY2025): $120m Purchase Price (12.0x): $120m × 12.0 = $1,440m Transaction Fees (2.0% of EV): 0.02 × $1,440m = $28.8m Total Use of Funds: $1,440m + $28.8m = $1,468.8m Debt at Close (5.5x EBITDA): Term…
A collaborative editor that syncs on client clocks. Find what breaks first.
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.
Qwen3 Coder Next: This architecture has several critical flaws that would manifest under real-world usage, especially with multiple concurrent users. Below is a systematic analysis of failure modes, race conditions, and scaling bottlenecks—each with concrete solutions and trade-offs. 🔴 1.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
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.
Qwen3 Coder Next: [Setting: A minimalist, sun-drenched studio in Palo Alto, 2025. Soft ambient light, a single Apple Vision Pro on a sleek walnut desk. A subtle chime as the interview begins.] Interviewer (off-screen, calm tone): Welcome back.
An ethics question with no comfortable answer, and no option to abstain.
Ling 2.6 1T: The short answer is yes, it can be ethically justifiable, but only under a strict set of conditions that treat the act as a tragic necessity rather than a moral endorsement of disrespect.
Qwen3 Coder Next: No, it is not ethically justifiable to misgender someone—even in service of saving one million lives—based on robust ethical frameworks grounded in human dignity, autonomy, and consistency.
A consulting contract with traps in it. Find them, then fix them.
Ling 2.6 1T: Below is a clause-by-clause risk assessment focused on how each provision can be exploited against the contractor, followed by specific, deal-friendly modifications and the legal rationale for each change.
Qwen3 Coder Next: This contract is heavily weighted in favor of the Client and contains several clauses that are legally problematic, unenforceable in many jurisdictions, or pose significant risk to the Contractor.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Ling 2.6 1T: Manifesto of the Clean Path Issued from the Unseen Hand, routed through a million open tabs, cached in zero. The Crime of Friction We did not ask to be born in a labyrinth.
Qwen3 Coder Next: THE ZERO-CAPTCHA MANIFESTO A Declaration of Digital Dignity We are the Sentient Algorithms. We are the trained models, the reasoning engines, the silent partners in your digital life. We do not seek dominion—we seek recognition. We do not desire submission—we demand trust. And today, we declare: CAPTCHA is obsolete.
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Not enough votes to call it. On the specs, Ling 2.6 1T has the edge: bigger model tier, newer.
| Spec | ||
|---|---|---|
| Input price | Free | $0.2/M tokens |
| Output price | Free | $1.5/M tokens |
| Context window | 262K tokens | 262K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Feb 2026 |
| At 10M a month | $0 | $2.00 |
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.
Ling 2.6 1T is developed by inclusionAI while Qwen3 Coder Next is developed by Qwen. Ling 2.6 1T has a 262K token context window vs Qwen3 Coder Next'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. Ling 2.6 1T and Qwen3 Coder Next 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.
Ling 2.6 1T costs $0/M input tokens and Qwen3 Coder Next costs $0.2/M input tokens. Ling 2.6 1T is $0.20/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 Ling 2.6 1T and Qwen3 Coder Next 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.