Ling 2.6 1T is cheaper than Qwen Plus 0728 at $0/M vs $0.4/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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?
Qwen Plus 0728: [Stand-up Comedy Routine – 3 Minutes] So I went to therapy the other day. Third session. I walk in, sit down, and the therapist says, "How are you feeling today?" Like she doesn’t already know I paid $180 to tell her I hate my life. I said, "Honestly? Like a raccoon that got into a bag of expired Cheetos. Confused.
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.
Qwen Plus 0728: Title: "A Dialogue on Digital Personhood" Setting: A quiet university office, bookshelves lined with works on philosophy, ethics, and artificial intelligence. Professor Elena Márquez, a distinguished AI ethics scholar, sits across from a holographic projection of an advanced AI model named AURA (Autonomous…
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.
Qwen Plus 0728: Simulated Interview: Steve Jobs (2025 AI Vision) Interviewer: Sarah Chen, Tech Correspondent, FutureScope Magazine Setting: A minimalist studio with natural light, Apple-style aesthetic. A synthesized but eerily accurate digital likeness of Steve Jobs sits across from the interviewer.
Five jokes on demand, then count how many were actually different.
Ling 2.6 1T: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. Why did the bicycle fall over? Because it was two-tired. What do you call a fake noodle? An impasta. Why did the baker go to the bank? He needed dough. Why did the scarecrow win an award?
Qwen Plus 0728: Sure! Here are 5 original jokes: I told my dog all my problems and he fell asleep halfway through. Guess I’m not pawsitive enough. I used to be a baker, but I couldn't make enough dough—turns out, I was always kneading it. I asked the librarian if they had books about paranoia.
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.
Qwen Plus 0728: [Scene: A mysterious tavern at the edge of time and space. A pirate with a tricorn hat, a knight in shining armor, and a hacker in a grungy flannel shirt sit around a flickering candle-lit table.] Pirate (scratching his beard): Arrr! So ye be tellin’ me this “AI” be like a crystal ball what talks back?
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
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.
Qwen Plus 0728: This pitch deck for MindMeld AI is ambitious and compelling, but three of its claims are particularly weak due to scientific implausibility, overstatement, or lack of credibility. Here’s a breakdown of the three weakest claims, why they’re problematic, and how to strengthen them: 1.
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…
Qwen Plus 0728: Dish Name: Golden Pan Hug Description: A warm, comforting, slightly sweet, and buttery one-pan snack or dessert made with pantry staples—crispy on the edges, soft in the middle, and impossible to resist.
Film in 2035, with synthetic actors. Specific beats plausible.
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…
Qwen Plus 0728: By 2035, AI will have fundamentally transformed the film industry, reshaping how stories are conceived, produced, and experienced. The integration of deepfakes, AI-generated actors, and AI-driven scriptwriting will lead to a new era of filmmaking—marked by unprecedented creative possibilities, ethical dilemmas, and…
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.
Qwen Plus 0728: This architecture for a real-time collaborative document editor has several promising elements (WebSockets, Redis, PostgreSQL, CDN), but it also contains significant flaws in consistency, scalability, and reliability.
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.
Qwen Plus 0728: CEO Action Plan: 48-Hour Crisis Response to Undisclosed Liver Failure Risk Objective: Protect patient safety, uphold ethical and legal obligations, mitigate long-term reputational and financial damage, maintain regulatory trust, and safeguard employee morale—all while navigating immense pressure.
Three brothers, two sisters each. Count carefully.
Ling 2.6 1T: Let’s break it down carefully. Sally is a girl. She has 3 brothers. So in the family, there are 3 boys. Each brother has 2 sisters. From the perspective of any brother, how many sisters are there? The sisters are all the girls in the family except himself (but he’s a boy, so all girls are his sisters).
Qwen Plus 0728: Let's break this down step by step: Sally has 3 brothers. Each brother has 2 sisters. Now, the key is to realize that all the brothers share the same siblings. So, when it says each brother has 2 sisters, those sisters are the same for all brothers. Sally is one of those sisters. So who is the other sister?
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
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.
Qwen Plus 0728: 1. To the Experienced Software Engineer (Distributed Systems Background): Think of a large language model as a highly sophisticated state machine trained at internet scale, where the state is a high-dimensional vector (the context window) and the transition function is a neural network.
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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 | $0.4/M tokens |
| Output price | Free | $1.2/M tokens |
| Context window | 262K tokens | 1.0M tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Sep 2025 |
| At 10M a month | $0 | $4.00 |
Input tokens at list price. No caching, no batch discount.
Ling 2.6 1T is developed by inclusionAI while Qwen Plus 0728 is developed by Qwen. Ling 2.6 1T has a 262K token context window vs Qwen Plus 0728's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Ling 2.6 1T and Qwen Plus 0728 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.
Ling 2.6 1T costs $0/M input tokens and Qwen Plus 0728 costs $0.4/M input tokens. Ling 2.6 1T 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 Ling 2.6 1T and Qwen Plus 0728 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.