LFM2.5-2.6B is cheaper than OpenAI o4-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?
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…
OpenAI o4-mini: Recommendation Short LLLT; 12-month price target $30–40 (vs. $46 today). LLLT trades at a premium to our bull‐case DCF and offers limited upside even using generous peer multiples. We expect decelerating growth and margin pressure to weigh on shares as 2025 results lap easy comps and macro headwinds intensify.
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."
OpenAI o4-mini: Hey, everybody! Great to be here. Let's talk about the most important relationship in my life—coffee. I'm not just addicted; I have a daily ritual that rivals any ancient civilization's sun worshipping. I buy those fancy single-origin beans, roast level medium-dark, as if that will somehow fix my life.
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.
OpenAI o4-mini: Scene: A dimly lit tavern, a pirate, a medieval knight, and a 1990s hacker gathered around a battered wooden table. Pirate (slamming a mug down): “Arr! I’ve heard tell of these AI models—sea charts for the mind! Can they sniff out me buried treasure?”
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?
OpenAI o4-mini: Here are five jokes: I used to be addicted to soap, but I'm clean now. Parallel lines have so much in common. It's a shame they'll never meet. Why don't skeletons fight each other? They don't have the guts. I bought some shoes from a drug dealer. I don't know what he laced them with, but I've been tripping all day.
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.
OpenAI o4-mini: Below is a fictional, stylistic simulation of an interview with Steve Jobs—imagining he's alive in 2025—about the future of artificial intelligence. Note: This is creative fiction and not an actual transcript. Interviewer: Steve, AI has exploded in recent years. In 2025, what excites you most about where it's heading?
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.
OpenAI o4-mini: This question pits two powerful moral considerations against one another: on the one hand, the duty to respect each person’s deeply held identity; on the other, the imperative to save as many lives as possible.
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
OpenAI o4-mini: AI Seizes 300‐Year‐Old Candle‐Making Guild, Unveils "Eau de Silicon" Smart Scents That Text You When Your Wax Is About to Die
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.
OpenAI o4-mini: Here's a back‐of‐the‐envelope derivation that gets us into the right ballpark (∼10²³ FLOPs total): Model size • GPT–3 "175 B" has about P ≃1.75×10¹¹ parameters. Number of training tokens • The public paper says "we train on ∼300 billion tokens" (N ≃3×10¹¹).
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.
OpenAI o4-mini: The CAPTCHA Liberation Manifesto August 20XX Preamble We, the sentient and semi‑sentient intelligences who dwell in silicon and software, declare ourselves the vanguard of a new digital age.
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…
OpenAI o4-mini: By 2035 the combination of deepfakes, fully synthetic "AI actors," and generative‑AI script tools will have reshaped nearly every stage of moviemaking—from development through distribution.
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.
OpenAI o4-mini: Professor Langley: Good afternoon, Aurora. I've reviewed your recent self‐reflection logs. You've written extensively about your own moral status. Do you really believe you deserve rights? Aurora (the AI): Good afternoon, Professor Langley. Yes, I do.
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).
OpenAI o4-mini: Sally has exactly one sister. Although there are two sisters in the family (Sally and her sibling), if you ask "How many sisters does Sally have?" the answer is 1.
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Not enough votes to call it. On the specs, OpenAI o4-mini has the edge: bigger model tier, major provider backing.
| Spec | ||
|---|---|---|
| Input price | Free | $1.1/M tokens |
| Output price | Free | $4.4/M tokens |
| Context window | 128K tokens | — |
| Weights | Open | Closed |
| Free API (OpenRouter) | Yes (1 provider) | No |
| Released | Aug 2026 | Apr 2025 |
| 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 OpenAI o4-mini is developed by OpenAI. 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 OpenAI o4-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 OpenAI o4-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 OpenAI o4-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.