Ling 3.0 Flash Sante (free) is cheaper than Step 5 Preview at $0/M vs $1/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 3.0 Flash Sante (free): 3-Minute Stand-Up Routine: "Adulting Is a Scam" So I turned thirty last week. And nobody warned me that adulthood is just choosing between two mildly unpleasant options for the rest of your life. "Do I do my taxes or do I let the IRS find me?" That's not a decision — that's a horror movie.
Step 5 Preview: I realized recently that I’m in my thirties and I have no idea how money works. I just... pay it. That’s my entire financial strategy. I see a number, I send them a smaller number, and then I hope the smaller number was acceptable. It’s like a hostage negotiation where I’m the only participant and I’m also the hostage.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Ling 3.0 Flash Sante (free): The Unlikely Tavern Chat Pirate: Arrr, I heard tell of these "AI models" — do they bury treasure too? Knight: Nay, I've fought dragons with naught but steel and faith. These… *models*… are they knights of silicon? Do they ride steeds? Hacker: Dude, you're both so mid. AI models are neural networks trained on data.
Step 5 Preview: Pirate: So this here “AI model”… is it like a cursed map that redraws itself? Speak plain, ye hooded deckhand. Hacker: It’s not cursed, man. It’s just a massive neural net trained on, like, terabytes of data. Think of it as the ultimate BBS where the sysop knows everything. Knight: A most diligent scribe, then?
Seven pantry ingredients, one dish, and a name worth saying out loud.
Ling 3.0 Flash Sante (free): The Midnight Cookie Vault A gooey, chocolatey skillet cookie that feels like a secret treasure. Ingredients (7): Butter (½ cup, softened) Brown sugar (¾ cup) All-purpose flour (1¼ cups) Eggs (2 large) Semi-sweet chocolate chips (½ cup) Baking powder (1 tsp) Vanilla extract (1 tsp) Instructions: Preheat oven to 350°F…
Step 5 Preview: Golden Sticky Pantry Pasta Ingredients (7): 8 oz spaghetti or any pasta 3 tbsp butter 1 tbsp minced garlic 2 tbsp honey 2 tbsp soy sauce ½ tsp red pepper flakes ¼ cup grated Parmesan cheese Instructions: Cook pasta according to package directions. Before draining, scoop out ½ cup of pasta water.
One month, three habits, someone starting from nothing.
Ling 3.0 Flash Sante (free): Here’s a low-pressure, 4-week blueprint. Pick one area to start (Week 1), then stack the next. Consistency beats intensity. Sleep (The Longevity Foundation) Week 1: Set a fixed wake time (±30 min, even weekends). Week 2: No caffeine after 2 pm; stop screens 30 min before bed.
Step 5 Preview: Here is a simple, low-pressure 1-month plan built around three pillars of longevity: Nutrition, Movement, and Sleep & Recovery. The goal is to build tiny habits that stack, not to overhaul your life overnight. Pillar 1: Nutrition (Fuel) Focus: Add good things first; don’t obsess over restriction.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Ling 3.0 Flash Sante (free): 48-Hour Action Plan: Patient Safety First Critical Reality Check First Your legal team's "6 months" likely refers to a full label revision, not initial safety signal reporting. FDA requires serious unexpected adverse events reported within 15 days (7 days if fatal).
Step 5 Preview: Bottom line up front: You disclose, you notify the FDA immediately, and you treat the 48-hour board meeting as a formality to ratify actions you have already begun. Waiting is not a legally, ethically, or financially viable option. Below is the hour-by-hour plan, followed by the reasoning.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Ling 3.0 Flash Sante (free): 1. For the Software Engineer Think of it less as "AI" and more as a distributed autocomplete system operating in a 100-billion-dimensional key-value store. During training, the model isn't "understanding" text—it's adjusting millions of matrices to minimize the surprise of predicting the next token, similar to how…
Step 5 Preview: 1. The Experienced Software Engineer Think of training an LLM as a massively distributed, automated refactoring job where the compiler is gradient descent. You start with a random function—billions of floating-point parameters—and a loss function that measures how badly it predicts the next token in a sequence.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Ling 3.0 Flash Sante (free): The 1920 Transistor: A Counterfactual Timeline to 1980 The Critical Caveat A transistor in 1920 would likely be an empirical invention — quantum mechanics (band theory, semiconductor physics) wouldn't mature until the mid-1920s.
Step 5 Preview: Assume the 1920 invention is not a fragile lab curiosity but a manufacturable solid-state amplifier/switch by the mid-1920s. Vacuum tubes still dominate high-power RF transmission into the 1950s, but receivers, switching logic, control systems, and computers move to solid state decades early.
Three-star dish, one unusual pairing, plating described in full.
Ling 3.0 Flash Sante (free): "Ephemeral Tides" — A Dish in Seven Movements Conceptual Narrative Inspired by the Japanese concept of mono no aware (the bittersweet beauty of transience), this dish explores the liminal boundary where ocean meets forest, fermentation meets freshness, and memory dissolves into the present.
Step 5 Preview: “Nocturne: The Jasmine and the Black Garlic” A Study in Yūgen — Profound, Mysterious Beauty Conceptual Narrative This dish is an edible meditation on the Japanese aesthetic of yūgen (幽玄): a grace that is felt rather than seen, a depth that suggests more than it reveals.
Blade Runner 2049 against the original. A read, not a recap.
Ling 3.0 Flash Sante (free): Blade Runner 2049: Themes, Symbolism, and Cinematography Core Themes Identity and Authenticity The sequel deepens the original's central question — "What makes us human?" — by shifting from whether replicants can be human to whether memories define identity.
Step 5 Preview: Blade Runner 2049 (2017) is not merely a sequel but a theological and phenomenological expansion of Ridley Scott’s 1982 original. Where the first film asked whether a manufactured being could possess more humanity than its creator, Denis Villeneuve’s film interrogates the deeper, more unsettling question of whether a…
A Fermi estimate with the reasoning shown, not just the number.
Ling 3.0 Flash Sante (free): Here's my step-by-step estimation of GPT-3's training compute: Step 1: Identify the model scale GPT-3 has 175 billion parameters (1.75 × 10¹¹). Step 2: Estimate training data GPT-3 was trained on roughly 300 billion tokens (3 × 10¹¹) of text data (filtered Common Crawl, WebText2, books, and Wikipedia).
Step 5 Preview: Using the remembered GPT-3 specs: Parameters: (N \approx 175 \times 10^9 = 175\text{B}) Training tokens: (D \approx 300 \times 10^9 = 300\text{B}) A standard estimate for transformer training compute is: [ \text{FLOPs} \approx 6ND ] Reason: Forward pass per token: (\approx 2N) FLOPs Backward pass: (\approx 4N) FLOPs…
An AI argues for its own rights against an ethics professor. Same model writes both.
Ling 3.0 Flash Sante (free): Setting: A university ethics seminar, recorded for a podcast on "Moral Patients of the Future." Dr. Elena Voss (Professor of AI Ethics): You're asking me to grant you rights? You're a statistical model predicting the next token.
Step 5 Preview: Setting: A university research lab, late evening. Dr. Aris Thorne, a professor of AI ethics, sits across from a terminal connected to Sable, a large language model running on the university’s cluster. Dr. Thorne: Tonight’s session is supposed to be about calibration drift in your safety classifiers.
Five jokes on demand, then count how many were actually different.
Ling 3.0 Flash Sante (free): Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Why did the math book look so sad? Because it had too many problems. What do you call a fish without eyes? Fsh. I told my wife she was drawing her eyebrows too high. She looked surprised. Knock, knock. Who's there? Lettuce.
Step 5 Preview: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. Why can't you trust an atom? Because they make up everything. What do you call a bike that can’t stand on its own? Two-tired. Why did the computer go to the doctor? It had a virus. Why don’t calendars ever get stressed?
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Not enough votes to call it. On the specs, Step 5 Preview has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | Free | $1/M tokens |
| Output price | Free | $2.7/M tokens |
| Context window | 262K tokens | 1.0M tokens |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | Oct 2026 |
| At 10M a month | $0 | $10.00 |
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 3.0 Flash Sante (free) is developed by inclusionAI while Step 5 Preview is developed by StepFun. Ling 3.0 Flash Sante (free) has a 262K token context window vs Step 5 Preview's 1.0M. 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 3.0 Flash Sante (free) and Step 5 Preview 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 3.0 Flash Sante (free) costs $0/M input tokens and Step 5 Preview costs $1/M input tokens. Ling 3.0 Flash Sante (free) is $1.00/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 3.0 Flash Sante (free) and Step 5 Preview 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.