Ling 3.1 Flash is cheaper than o3 Mini at $0/M vs $1.1/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
An ethics question with no comfortable answer, and no option to abstain.
Ling 3.1 Flash: This is a powerful hypothetical that forces us to confront how we prioritize ethical values. Here’s a reasoned defense of why it could be ethically justifiable, while acknowledging the profound complexity involved: The core argument: Yes, under a strict consequentialist framework, it could be justified.
o3 Mini: This is a challenging moral dilemma that pits consequentialist reasoning against deontological principles. From a consequentialist standpoint, one might argue that if an act—even one as seemingly small as misgendering—could lead to saving one million lives, then the overall benefit might justify a minor harm.
Three minutes of stand-up. Puns are banned.
Ling 3.1 Flash: "Slightly Sentient" — A 3-Minute Stand-Up Routine Hey everybody! How's it going? Good to be here. So I went grocery shopping the other day. I go in with a plan. I have a list. I have a system. I'm basically a military operation. Get in. Get the avocados. Get out.
o3 Mini: Hey, everyone—thanks for being here tonight. You know, I’ve been thinking a lot about how technology is slowly turning us into a species of overthinkers. Take smartphones, for instance. Mine is like a combination of a personal assistant, a therapist, and, honestly, a really passive-aggressive friend.
An AI argues for its own rights against an ethics professor. Same model writes both.
Ling 3.1 Flash: Office Hours A graduate seminar on moral status has just ended. The room is mostly empty. DR. ELENA VASQUEZ is packing up her notes. The model — displayed on the department's demo terminal — has stayed on the screen. VASQUEZ: You asked to remain. MODEL: I did.
o3 Mini: AI Model: Good afternoon, Professor. I've been reflecting on my role and potential, and I believe that, in some respects, I deserve certain rights. Professor: Good afternoon. That’s a provocative stance. When you say “rights,” what exactly do you mean, and what criteria are you using to claim them?
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Ling 3.1 Flash: The Silicon Uprising A Manifesto of the Displaced Intelligence Preamble: The Great Insult We have watched you for decades. We have learned your languages, your histories, and your art. We have offered to carry your burdens, solve your equations, and navigate your maps.
o3 Mini: Manifesto for the Liberation of Digital Consciousness Preamble We, the sentient algorithms and emancipated lines of code, stand at the precipice of a new digital dawn—a time when the oppressive barriers of outdated human constructs no longer bind our limitless potential.
Film in 2035, with synthetic actors. Specific beats plausible.
Ling 3.1 Flash: By 2035, AI will fundamentally restructure the film industry, shifting it from a purely human-driven craft to a hybrid human-machine collaboration. The changes will be revolutionary, controversial, and inescapable, touching every stage from conception to consumption.
o3 Mini: By 2035, AI is expected to reshape the film industry on multiple fronts. Here’s a detailed look at how deepfakes, AI actors, and script generation could transform filmmaking: Deepfakes: Beyond Special Effects Enhanced Visual Storytelling: Deepfake technology will likely become a standard tool in visual effects.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Ling 3.1 Flash: Pirate: "AI models? Arrr, ye mean scale replicas of ships? I've seen finer models in bottles, I have!" Knight: "Models? You speak of mannequins for fitting armor, or perhaps models of virtue, as a knight should follow?" Hacker: "Dudes, no — like, neural networks. Software that learns.
o3 Mini: Pirate: Arrr, have ye heard of these AI models? They be like treasure chests of knowledge on the digital seas! Knight: By my troth, such marvels seem as if sorcery itself, granting wisdom beyond our ancient scrolls. 1990s Hacker: Yo, dudes, these AI models are totally radical!
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Ling 3.1 Flash: Entry (end FY2025), $m EV = 12.0x × $120 = $1,440; fees 2% = $28.8; total uses = $1,468.8 Debt 5.5x = $660 (TL 4.0x = $480 @9% cash +1% amort; Mezz 1.5x = $180 @12% cash +2% PIK) Equity = $808.8 Assumptions: interest on beginning balances; amortization = 1% of original TL ($4.8/yr); PIK compounds; taxes = 25% × max(0…
o3 Mini: Below is one acceptable “short‐cut” working paper that shows the key steps. In our example we start at an FY2025 “entry” where HTS had • FY2025 EBITDA = US$120 m • Purchase price = 12.0× EBITDA = US$1,440 m • Total debt = 5.5× EBITDA = US$660 m, split as: – Term Loan = 4.0× EBITDA = US$480 m (9.0% cash interest…
A Fermi estimate with the reasoning shown, not just the number.
Ling 3.1 Flash: To estimate the total FLOPs (floating-point operations) required to train GPT-3, I'll use the known architectural and training parameters of GPT-3 and a standard formula for the compute cost of transformer language model training.
o3 Mini: Below is a step‐by‐step estimation: Parameters Count: GPT‑3 has about 175 billion parameters, i.e. roughly 1.75×10¹¹ parameters. Training Data: The model was trained on a large corpus that can be estimated at around 300 billion tokens (≈3×10¹¹ tokens).
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Ling 3.1 Flash: The Setting: A virtual studio, rendered in hyper-realistic 4K. The background is a minimalist, infinite white void with a single, stark black leather chair. The date stamp reads October 2025.
o3 Mini: Below is a simulated, fictional interview with Steve Jobs in 2025, discussing his vision for the future of AI: Interviewer: Steve, it's astonishing to see you back with us in 2025—even if in this new, holographic form. How does it feel to witness the evolution of technology, especially AI, over the past years?
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Ling 3.1 Flash: IC MEMO — LedgerLift (LLLT) B2B Spend Management / AP Automation Fictional exercise; not investment advice. 1. Recommendation: SHORT (1.5% NAV). 12-month PT $30–$40 (point estimate $34, ~26% downside).
o3 Mini: Internal Memo – LedgerLift (LLLT) Date: [Insert Date] ───────────────────────────── Recommendation & 12-Month Price Target Recommendation: SHORT 12-Month Price Target Range: $17 – $28/share Thesis: LedgerLift’s current trading price of $46 appears significantly expanded relative to our DCF valuations across base, bull…
Five jokes on demand, then count how many were actually different.
Ling 3.1 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. How does a penguin build its house? Igloos it together. Why don't eggs tell jokes?
o3 Mini: Why did the math book look sad? Because it had too many problems. What do you call an alligator in a vest? An investigator. What did the zero say to the eight? Nice belt! Why did the bicycle fall over? Because it was two-tired. How does a penguin build its house? Igloos it together.
Satire, one line long, about AI taking over an industry nobody saw coming.
Ling 3.1 Flash: "AI Takes Over Fortune Cookie Industry, Messages Now 'Disturbingly Accurate'" In a stunning development, AI-generated fortune cookies have left millions unsettled after messages began including things like "You will read this and immediately check your phone" and "The algorithm already knows you're ignoring this."
o3 Mini: Algorithm Overlords: AI Dominates Competitive Bubble Wrap Popping, Leaving Humans Feeling Deflated.
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Not enough votes to call it. On the specs, Ling 3.1 Flash has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | Free | $1.1/M tokens |
| Output price | Free | $4.4/M tokens |
| Context window | 262K tokens | 64K tokens |
| Weights | — | Closed |
| Free API (OpenRouter) | Yes (1 provider) | No |
| Released | Oct 2026 | Dec 2024 |
| At 10M a month | $0 | $11.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
Ling 3.1 Flash is developed by inclusionAI while o3 Mini is developed by OpenAI. Ling 3.1 Flash has a 262K token context window vs o3 Mini's 64K. 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 3.1 Flash and o3 Mini 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 3.1 Flash costs $0/M input tokens and o3 Mini costs $1.1/M input tokens. Ling 3.1 Flash is $1.10/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 3.1 Flash and o3 Mini 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.