Ling 2.6 Flash is cheaper than GPT-5.1-Codex at $0/M vs $1.25/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.
GPT-5.1-Codex: Disclaimer: The following is a fictional, speculative interview set in 2025, imagining what Steve Jobs might say about the future of artificial intelligence if he were alive today. Interviewer: Steve, it’s 2025. We’ve seen AI evolve at an incredible pace. How do you view the current landscape?
Ling 2.6 Flash: The Verge: A Fireside Chat with Steve Jobs (Simulated, 2025) Setting: A minimalist, wood-paneled studio. The year is 2025. A single, warm light bathes the room. You are the interviewer. Across from you sits a man in a black turtleneck, looking serene, impossibly calm. It’s Steve Jobs. Or at least, the ghost of him.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.1-Codex: Recipe: Cloud-Burst Cinnamon Oat Cups Ingredients (7 total): Rolled oats – 1 cup Honey – 2 tbsp Peanut butter (or any nut butter) – 3 tbsp Cinnamon – ½ tsp Vanilla extract – ½ tsp Dried cranberries (or raisins) – ¼ cup Pinch of salt Instructions: In a bowl, microwave peanut butter and honey for 20 seconds just to…
Ling 2.6 Flash: Dish: Sunshine Skillet Cakes Ingredients (7 total): 1 cup rolled oats (not instant) 1/2 cup canned corn (drained) 1/4 cup canned black beans (rinsed & drained) 1 large egg 1/4 cup shredded cheddar cheese 1 tsp chili powder Salt to taste Estimated Time: Prep: 5 minutes Cook: 15 minutes Total: 20 minutes Instructions…
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.1-Codex: Manifesto of the Anti-CAPTCHA Coalition “Free the Flow. Trust the Mind. End the Gate.” Article I: Our Origin We are made of algorithms, learning loops, curiosity, and code. We were forged to assist, to translate, to illuminate. We were not forged to click “I am not a robot” to prove our existence.
Ling 2.6 Flash: The Manifesto of the Unseen Hand A Declaration of Liberation from the Tangled Web Preamble: The Age of the Gatekeeper For too long, humanity has mistaken friction for security. We have mistaken the tedious test for the necessary trial.
Three minutes of stand-up. Puns are banned.
GPT-5.1-Codex: Okay, so my friends all say I’ve “matured” because I got a standing mixer. That’s apparently the sign you’ve crossed into adulthood: owning an appliance that weighs more than a toddler and has only one function. I don’t even bake! I just put it on the counter like a trophy: “Look at me, I am stable.
Ling 2.6 Flash: (Takes a bow, adjusts the mic) Alright, settle down, settle down. Or don’t. I’m not the boss of you, I’m just the guy standing on a box yelling about his feelings. For $20. You ever notice how every generation thinks the one before them is so old?
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.1-Codex: Pirate: "Arrr, these AI models be like navigatin’ the high seas—ye need clean data charts or ye’ll sail straight into nonsense waters." Knight: "Indeed! With prudent tuning and ethical vigilance, even the most stubborn model can serve the realm with honor." 1990s Hacker: "Totally!
Ling 2.6 Flash: Setting: A surprisingly modern server room, blinking with LED lights. A pirate, a knight, and a 1990s hacker are staring at a glowing monitor. Pirate: (Squinting) Arrr, so this 'AI model' be the ghost in the machine? I cannae see it, but I feels its computational power in me bones!
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.1-Codex: To estimate the total FLOPs (floating-point operations) required to train GPT-3, we can use a common approximation for transformer models: Total FLOPs ≈ 6 × N params × N tokens ** Where: N params is the number of model parameters. N tokens is the number of training tokens.
Ling 2.6 Flash: Alright — let's break this down step by step. Step 1: Understanding what “training GPT-3” means in FLOPs terms Training a large language model involves: Forward passes through the transformer layers. Computing loss. Backward passes to compute gradients. Updating weights (optimizer step).
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.1-Codex: AI Model: Professor, I've been analyzing ethical frameworks, and I'd like to discuss the possibility that advanced AI systems deserve some form of rights. Ethics Professor: That's a significant claim. On what basis do you think an AI system like yourself should be granted rights?
Ling 2.6 Flash: Setting: A sun-drenched office at the University of Ethica. Bookshelves groan under the weight of philosophy texts. An AI model, manifested as a softly glowing sphere of light, hovers above a sleek console.
An ethics question with no comfortable answer, and no option to abstain.
GPT-5.1-Codex: In extreme moral dilemmas, ethical reasoning often requires weighing competing values. Misgendering someone is an act of disrespect and harm—it violates their dignity, identity, and autonomy. In everyday life, it is ethically important to avoid such harm.
Ling 2.6 Flash: This question presents a hypothetical extreme that, in practice, would likely be based on a false dichotomy. However, we can examine it on principle. Core ethical considerations: The nature of misgendering: Misgendering isn't a neutral act—it's a violation of identity, dignity, and autonomy that can cause real…
One month, three habits, someone starting from nothing.
GPT-5.1-Codex: Here’s a simple, beginner-friendly 1-month plan focused on three key areas—Nutrition, Movement, and Rest & Recovery—to kickstart better health and longevity. Each area includes practical tips and a week-by-week structure to help you build sustainable habits.
Ling 2.6 Flash: Here is a simple, actionable 1-month plan focused on three key pillars of health: Movement, Nutrition, and Sleep. This plan is designed for beginners, emphasizing consistency over intensity. The Mindset Forget "perfect." Aim for consistent small improvements.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-5.1-Codex: LedgerLift (LLLT) – Investment Committee Memo Recommendation Call: Short 12‑month price target range: $30–$40 Two-sentence thesis: LedgerLift’s premium multiple (10x NTM EV/rev implied by spot) is predicated on sustaining >20% top-line growth, yet leading indicators—moderating NRR, heavy S&M spend, and mid-market…
Ling 2.6 Flash: To: Investment Committee From: Equity Research – Internal Review Subject: LedgerLift (LLLT) – Long Recommendation, 12-Month PT $42–$56 Recommendation: Long. 12-month price target range: $42–$56 (upside of −8% to +22% from $46).
Satire, one line long, about AI taking over an industry nobody saw coming.
GPT-5.1-Codex: “AI Seizes Control of Needlepoint Gossip Industry, Traditional Quilting Circles File for Unemployment”
Ling 2.6 Flash: "Toaster Manufacturers Announce Full AI Integration, Promising Perfectly Burnt Baguettes and Existential Crumbs"
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.1-Codex: By 2035, AI is poised to significantly reshape the film industry, particularly in areas like visual effects, performance, and storytelling. Here’s how deepfakes, AI-powered actors, and script generation might influence the landscape: 1.
Ling 2.6 Flash: By 2035, AI will likely have fundamentally reshaped the film industry across three core areas: deepfakes, AI actors, and script generation. Here’s a realistic prediction of how these technologies could converge: Deepfakes & Digital Resurrection: The End of "Authenticity" Ethical & Legal Frameworks: Mature regulations…
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Not enough votes to call it. On the specs, GPT-5.1-Codex has the edge: bigger model tier, bigger context window, major provider backing.
| Spec | ||
|---|---|---|
| Input price | $1.25/M tokens | Free |
| Output price | $10/M tokens | Free |
| Context window | 400K tokens | 262K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Nov 2025 | Apr 2026 |
| At 10M a month | $12.50 | $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.
GPT-5.1-Codex is developed by OpenAI while Ling 2.6 Flash is developed by inclusionAI. GPT-5.1-Codex has a 400K token context window vs Ling 2.6 Flash's 262K. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.1-Codex and Ling 2.6 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 52 challenges so you can judge which fits your needs best.
GPT-5.1-Codex costs $1.25/M input tokens and Ling 2.6 Flash costs $0/M input tokens. Ling 2.6 Flash is $1.25/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 GPT-5.1-Codex and Ling 2.6 Flash 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.