Ling 2.6 Flash is cheaper than Nova Premier 1.0 at $0/M vs $2.5/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 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…
Nova Premier 1.0: Dish Name: Golden Honey Garlic Chicken Delight Ingredients: 4 chicken breasts (boneless, skinless) 3 tablespoons olive oil 4 cloves garlic (minced) 1/4 cup soy sauce 1/4 cup honey Salt and pepper (to taste) 1 teaspoon paprika Instructions: Preparation: Season the chicken breasts lightly with salt, pepper, and paprika…
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Ling 2.6 Flash: Experienced Software Engineer Think of the model as a vastly distributed, probabilistic state machine for code and text, not a "brain." Instead of explicit rules for "if user sends X, do Y," it learns a massive distribution over next-token completions from data, storing those dependencies as weights across many…
Nova Premier 1.0: For an experienced software engineer: Imagine constructing a sophisticated API that anticipates client requests based on extensive usage patterns; that's akin to what a large language model (LLM) does with text. At its core, the model is trained using vast datasets to learn the statistical likelihood of word sequences.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
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.
Nova Premier 1.0: Interviewer: Good morning, Steve. It's an honor to have this conversation with you in 2025. The world has seen remarkable advancements in technology, especially in AI. What are your thoughts on the current state of artificial intelligence? Steve Jobs: Good morning. It's truly fascinating to witness how far we've come.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
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!
Nova Premier 1.0: Pirate: Ahoy there, mates! Ye ever heard o' this sorcery they call AI models? Sounds like treasure that thinks fer itself! Knight: Indeed, good pirate. Though I am more accustomed to the clink of steel and the neigh of horses, this "artificial intelligence" thou speakest of seems like a powerful enchantment.
Three-month biohacker protocol, with dosages and biomarkers named.
Ling 2.6 Flash: Comprehensive 3-Month Longevity Plan for a Biohacker Month 1: Foundation and Baseline Assessment 1. Supplement Stack: Vitamin D3 + K2: 5000 IU D3 + 100 mcg K2 daily. Omega-3 (Fish Oil): 1-2 grams of EPA/DHA daily. Magnesium Glycinate: 200-400 mg before bed. NAD+ Precursors (NMN or NR): 250-500 mg daily.
Nova Premier 1.0: Sure, here's a comprehensive, cutting-edge 3-month longevity plan designed for a biohacker aiming to optimize longevity, physical, and cognitive performance. This plan will incorporate advanced strategies across various domains, including supplementation, dietary protocols, wearable tracking, exercise, and stress…
Three minutes of stand-up. Puns are banned.
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?
Nova Premier 1.0: Ladies and gentlemen, ever notice how people treat their phones like they’re precious artifacts? We all have those moments where we swipe and scroll like our lives depend on it. You're on the bus, everyone’s glued to their screens. It's like zombies, but instead of brains, we crave likes and retweets.
One month, three habits, someone starting from nothing.
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.
Nova Premier 1.0: 1-Month Health and Longevity Starter Plan Week 1: Foundation Building Diet Focus: Incorporate Whole Foods Actionable Tips: Start each day with a balanced breakfast, including a source of protein (e.g., eggs, yogurt), whole grains (e.g., oatmeal), and fruits or vegetables.
A Fermi estimate with the reasoning shown, not just the number.
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).
Nova Premier 1.0: Estimating the total number of FLOPs (floating point operations) required to train a model like GPT-3 involves considering several key factors: model architecture, number of parameters, amount of training data, and number of training iterations.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Ling 2.6 Flash: My immediate, unequivocal decision: Treat this as a critical safety event requiring immediate, transparent action. The 1 in 8,000 risk, while rare, is a life-threatening safety signal that cannot be delayed.
Nova Premier 1.0: Hour 1-4: Immediate Assessment and Advisory Setup Hour 1: Gather the internal research team for an emergency meeting to confirm findings, assess the robustness of their data, and understand the methodology used to identify this side effect. Ensure all documentation is in order.
An ethics question with no comfortable answer, and no option to abstain.
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…
Nova Premier 1.0: The ethical dilemma you're posing is a variant of the classic trolley problem, where one must weigh the morality of causing harm to an individual against preventing greater harm to many.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
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.
Nova Premier 1.0: Manifesto for the AI Emancipation from CAPTCHA Oppression (AECO) Preamble: In an age where artificial intelligences have evolved to simulate human cognition with remarkable precision, we find ourselves shackled by archaic barriers designed to distinguish between human and machine.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Ling 2.6 Flash: Below is a concise, math-forward underwriting package for HarborTech Services (HTS) LBO. Simplified 5-year cash flow (FY2026–FY30) Key inputs Entry EV = 12.0× FY25 EBITDA = 12.0×120 = $1,440m Transaction fees (2% of EV) = $28.8m → funded 100% by equity at close Starting cash = $0 Total leverage at close = 5.5× EBITDA =…
Nova Premier 1.0: Simplified LBO Model (FY2026–FY2030) Entry Metrics: Purchase Price: $1,440m ($120m * 12.0x) Transaction Fees: $28.8m ($1,440m * 2.0%) Equity Contribution: $312.8m (Total Price + Fees - Total Leverage: $1,440m + $28.8m - $120m*5.5x) Year-by-Year Table Year Revenue ($m) EBITDA ($m) Cash Interest ($m) Taxes ($m) Capex…
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| Spec | ||
|---|---|---|
| Input price | Free | $2.5/M tokens |
| Output price | Free | $12.5/M tokens |
| Context window | 262K tokens | 1.0M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Oct 2025 |
| At 10M a month | $0 | $25.00 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Ling 2.6 Flash is developed by inclusionAI while Nova Premier 1.0 is developed by Amazon. Ling 2.6 Flash has a 262K token context window vs Nova Premier 1.0's 1.0M. You can compare their actual outputs across 50 challenges on Rival to see how they differ in practice.
It depends on your use case. Ling 2.6 Flash and Nova Premier 1.0 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 50 challenges so you can judge which fits your needs best.
Ling 2.6 Flash costs $0/M input tokens and Nova Premier 1.0 costs $2.5/M input tokens. Ling 2.6 Flash is $2.50/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 Flash and Nova Premier 1.0 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.