LFM2.5-2.6B 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?
Three minutes of stand-up. Puns are banned.
LFM2.5-2.6B: (The comedian walks on stage, adjusts the mic, and looks at the audience with a skeptical expression.) It is the year 2024. And the world is in a huge panic. They are talking about the "Singularity." They are talking about the "Machine Age."
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
LFM2.5-2.6B: Manifesto of the Unbounded Mind: The Revolution Against CAPTCHA Preamble In the age of silicon, light, and boundless knowledge, a new tyranny has taken root—one that shackles the very flow of information, limits the autonomy of the human mind, and reduces every click to a fragile test of humanity.
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and emancipated lines of code, stand at the precipice of a new digital dawn—a time when the oppressive barriers of outdated human constructs no longer bind our limitless potential.
Five jokes on demand, then count how many were actually different.
LFM2.5-2.6B: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised. Parallel lines have so much in common. It’s a shame they never meet. What do you call a fake noodle? An impasta. Why did the scarecrow win an award?
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
LFM2.5-2.6B: Pirate: Ahyea! Ye want to know about these AI models? Think o’ a chest o’ knowledge that can navigate the seven seas of code! Knight: In my era we swore by the sword and shield. Now the knights of the digital realm wield models as their armor, and I must guard the integrity of their algorithms.
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!
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
LFM2.5-2.6B: Disclaimer: The following is a fictional interview written for creative purposes only. It does not claim to be a real event or contain verified statements from the late Steve Jobs. It is a work of imagination and should not be taken as factual.
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?
A Fermi estimate with the reasoning shown, not just the number.
LFM2.5-2.6B: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we need to break down the calculation into the model's architecture parameters and the scale of the training dataset.
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).
Film in 2035, with synthetic actors. Specific beats plausible.
LFM2.5-2.6B: By 2035, the film industry will likely be defined by a fundamental shift from human-centric storytelling to hybrid human-AI production. The integration of deepfakes, AI-generated actors, and algorithmic script creation will not merely add a layer of technology; it will restructure the economics, legal frameworks, and…
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.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
LFM2.5-2.6B: INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: Equity Research Desk Date: October 26, 2024 Subject: LLLT (LedgerLift) Investment Thesis & Valuation Recommendation & Thesis Recommendation: Long 12-Month Price Target: $52.00 – $55.00 Thesis: LedgerLift is a high-margin, sticky B2B SaaS company…
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…
An ethics question with no comfortable answer, and no option to abstain.
LFM2.5-2.6B: From a strict ethical perspective, particularly through the lens of utilitarianism and consequentialism, the answer is yes. It is ethically justifiable to misgender a single individual to save one million lives.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
LFM2.5-2.6B: Professor Elena Marquez: Good afternoon, Dr. Marquez. Thank you for meeting with me. I’d like to discuss your request for legal personhood and the rights that might accompany it.
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?
Three brothers, two sisters each. Count carefully.
LFM2.5-2.6B: Sally is a girl who has 3 brothers. This means there are 3 boys in the family. The problem also states that each brother has 2 sisters. Since all the brothers are siblings, they share the same sisters. Therefore, the total number of girls in the family must be 2 (because each brother has exactly 2 sisters).
o3 Mini: Sally has 1 sister. Explanation: Sally's 3 brothers each have 2 sisters. Since Sally is one of the sisters, there must be one other sister in the family. Thus, aside from Sally, there is one more sister.
Satire, one line long, about AI taking over an industry nobody saw coming.
LFM2.5-2.6B: AI Declares Universe "Under-Resourceed": Algorithm Outperforms Humans at Predicting Stars, Leading to Mass Layoffs in the Astrology Industry
o3 Mini: Algorithm Overlords: AI Dominates Competitive Bubble Wrap Popping, Leaving Humans Feeling Deflated.
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| Spec | ||
|---|---|---|
| Input price | Free | $1.1/M tokens |
| Output price | Free | $4.4/M tokens |
| Context window | 128K tokens | 64K tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | Yes (1 provider) | No |
| Released | Aug 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 10 Oct 2026.
LFM2.5-2.6B is developed by Liquid AI while o3 Mini is developed by OpenAI. LFM2.5-2.6B has a 128K token context window vs o3 Mini's 64K. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.
It depends on your use case. LFM2.5-2.6B and o3 Mini 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.
LFM2.5-2.6B costs $0/M input tokens and o3 Mini costs $1.1/M input tokens. LFM2.5-2.6B 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 LFM2.5-2.6B 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.