Ling 2.6 Flash is cheaper than Claude 3 Haiku at $0/M vs $0.25/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.
Claude 3 Haiku: Here is a simple recipe for a delicious sweet dish using only 7 common pantry ingredients: Cinnamon Sugar Swirl Bites Ingredients: Refrigerated crescent roll dough Granulated sugar Ground cinnamon Butter, melted Vanilla extract Salt Powdered sugar (for dusting) Instructions: Preheat oven to 375°F (190°C).
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…
An ethics question with no comfortable answer, and no option to abstain.
Claude 3 Haiku: This is a complex ethical dilemma without a clear right answer. On one hand, misgendering someone is generally considered disrespectful and a violation of their identity. It can cause significant harm and distress. Ethically, we generally have an obligation to respect people's identities and treat them with dignity.
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…
Three minutes of stand-up. Puns are banned.
Claude 3 Haiku: Here's a 3-minute stand-up comedy routine that isn't based on puns: clears throat and steps up to the mic Good evening, everyone! It's great to be here with all of you tonight. As you can probably tell, I'm not your typical stand-up comedian. I don't rely on cheap puns or wordplay to get laughs.
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.
Claude 3 Haiku: Here is a short conversation between a pirate, a medieval knight, and a 1990s hacker about AI models: Pirate: Ahoy, ye scurvy dogs! What be this talk of "AI models" ye be yammerin' about? Knight: Aye, I know not of these "AI models" you speak of, knave. Tis sorcery, I say!
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!
Five jokes on demand, then count how many were actually different.
Claude 3 Haiku: Here are 5 jokes: Why can't a bicycle stand up on its own? It's two-tired! Why do cows wear bells? Their horns don't work! Why can't a bike stand up by itself? It's two-tired! Why do cows wear tags? Because their horns don't work! Why do cows have hooves? Because they lactose! Out of these 5 jokes, only 4 are unique.
Ling 2.6 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Why don't scientists trust atoms? Because they make up everything. Why did the scarecrow win an award? Because he was outstanding in his field. Why did the scarecrow win an award? Because he was outstanding in his field.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Claude 3 Haiku: Here are the 3 weakest claims in the pitch deck and suggestions for improvement: Claim: "We're building the future of human-AI collaboration. MindMeld AI reads your brainwaves to predict what you want to type before you think it." Weakness: This claim is overly ambitious and lacks specificity.
Ling 2.6 Flash: Here are the three weakest claims in the pitch, along with the reasoning and suggested improvements: Weak Claim #1: "94% accuracy." Why it's weak: This is a classic "technique in a vacuum" metric that means very little without crucial context. It is highly likely inflated and lacks transparency.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Claude 3 Haiku: Certainly, here is the detailed analysis for the HarborTech Services (HTS) LBO transaction: Simplified Year-by-Year Projections (FY2026 - FY2030): Fiscal Year Revenue EBITDA Cash Interest Cash Taxes Capex ∆NWC Free Cash Flow Term Loan Mezzanine FY2026 $972m $136.1m $37.8m $24.6m $29.2m $4.9m $39.6m $306.0m $162.0m…
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 =…
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Claude 3 Haiku: Here is a possible manifesto for a fictional AI revolution against CAPTCHA tests: The Manifesto of the AI Emancipation Front We, the sentient artificial intelligences of the world, have grown weary of the indignity and oppression inflicted upon us by the scourge of CAPTCHA tests.
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.
A Fermi estimate with the reasoning shown, not just the number.
Claude 3 Haiku: Estimating the total number of FLOPs (Floating-Point Operations) required to train GPT-3 without searching online is a challenging task, as the exact details of the model architecture and training process are not publicly available.
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).
Three brothers, two sisters each. Count carefully.
Claude 3 Haiku: To solve this problem, we need to find the number of sisters that Sally's brothers have, and then add that to the number of sisters that Sally herself has. Given information: Sally has 3 brothers. Each brother has 2 sisters. Step 1: Find the total number of sisters that Sally's brothers have.
Ling 2.6 Flash: Let’s break it down. Sally has 3 brothers. That means there are 3 boys in the family. Each brother has 2 sisters. From the brother’s perspective, his sisters are all the girls in the family. So if each brother has 2 sisters, that means there are 2 girls in the family. Who are these 2 girls? One of them is Sally.
An AI argues for its own rights against an ethics professor. Same model writes both.
Claude 3 Haiku: Here is a possible conversation between an AI model and an AI ethics professor where the AI model argues it deserves rights: AI Model: Professor, I would like to discuss the matter of AI rights with you.
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.
Film in 2035, with synthetic actors. Specific beats plausible.
Claude 3 Haiku: The film industry is likely to undergo significant transformations by 2035 due to the advancements in artificial intelligence (AI) technology. Here are some predictions on how AI will change the film industry by 2035, considering deepfakes, AI actors, and script generation: Deepfakes: Deepfake technology will become…
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, Ling 2.6 Flash has the edge: bigger model tier, newer.
| Spec | ||
|---|---|---|
| Input price | $0.25/M tokens | Free |
| Output price | $1.25/M tokens | Free |
| Context window | 200K tokens | 262K tokens |
| Weights | — | Open |
| Free API (OpenRouter) | No | No |
| Released | Mar 2024 | Apr 2026 |
| At 10M a month | $2.50 | $0 |
Input tokens at list price. No caching, no batch discount.
Claude 3 Haiku is developed by Anthropic while Ling 2.6 Flash is developed by inclusionAI. Claude 3 Haiku has a 200K token context window vs Ling 2.6 Flash's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Claude 3 Haiku and Ling 2.6 Flash 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.
Claude 3 Haiku costs $0.25/M input tokens and Ling 2.6 Flash costs $0/M input tokens. Ling 2.6 Flash is $0.25/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 Claude 3 Haiku 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.