Skip to content
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed
  1. Home/
  2. Compare/
  3. LFM2.5-2.6B vs Mercury 2.5 Preview
Updated Aug 2026

LFM2.5-2.6B vs Mercury 2.5 Preview

LFM2.5-2.6B is cheaper than Mercury 2.5 Preview at $0/M vs $0.04/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
LFM2.5-2.6B
Loading the build
Mercury 2.5 Preview

Which answer wins?

Written rounds

23 prompts
  • 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…

    Mercury 2.5 Preview: By 2035, cinema will undergo a profound transformation. Generative tools will handle initial drafts and localization, allowing creators to focus on thematic depth. Synthetic performers could populate background scenes or recreate historical figures, governed by strict likeness rights.

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: Pirate: "Arrgh! This ship sails faster than any wind I know, matey. It cuts the waves without a single sail." Knight: "By my oath, it moves with uncanny speed. But does it possess the strength to stand against a dragon's fire?" Hacker: "It's not about strength, it's about architecture.

    Every model's answer to this prompt
  • 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."

    Mercury 2.5 Preview: (Hey, thanks for coming out.) I’ve been thinking a lot about my house lately. Specifically, how it’s trying to run my life. I bought a smart speaker. Just a little cylinder. I thought it would be nice. Play music when I ask. But now it talks back. Not in a creepy way, just in a passive-aggressive way.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    LFM2.5-2.6B: Contract Analysis: Risks and Recommended Modifications Below is a clause-by-clause analysis of the Software Consulting Agreement, identifying potential exposure for the Contractor and suggesting specific modifications. SCOPE Clause Text: "Contractor shall provide software development services as directed by Client.

    Mercury 2.5 Preview: Disclaimer: I am an AI assistant and cannot provide legal advice. Consult a qualified attorney before signing any contract. Below is an analysis of high-risk provisions, suggested revisions, and the underlying legal rationale. Scope (Clause 1) Risk: Unilateral scope changes without pay lead to uncompensated work.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    LFM2.5-2.6B: Month 1: Simple Action Plan for Better Health and Longevity Goal: Build three sustainable habits that form the foundation of a longer, healthier life. Focus on diet, exercise, and sleep, with small, daily actions that compound over time. 1.

    Mercury 2.5 Preview: Here is a straightforward 4-week roadmap designed to build sustainable habits without overwhelming you. Core Pillars Nutrition: Focus on whole foods and hydration. Activity: Prioritize consistent movement over intensity. Restoration: Protect sleep quality and manage energy.

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    LFM2.5-2.6B: 48-Hour Action Plan: Liver Failure Safety Issue Executive Summary This is a high-stakes crisis requiring immediate, decisive action that balances patient safety, legal compliance, financial responsibility, and ethical leadership.

    Mercury 2.5 Preview: This is a critical governance and safety scenario. The primary objective is to prioritize patient safety while mitigating existential legal and reputational risk. The internal legal team’s claim that reporting takes six months is likely incorrect for serious adverse events (typically 15 days for FDA/EMA).

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    LFM2.5-2.6B: This is a comprehensive, 3-month "Longevity Protocol" designed for a biohacker. It integrates chronobiology, metabolic engineering, neurocognitive optimization, and performance science.

    Mercury 2.5 Preview: Disclaimer: I am an AI assistant, not a medical professional. The following plan is for informational purposes only. Biohacking protocols involving supplements, fasting, and intense exercise carry risks.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    LFM2.5-2.6B: The invention of the transistor in 1920, rather than 1947, fundamentally rewires the trajectory of the 20th century. The pivotal difference is not the year of invention, but the 23 years of head start provided for the semiconductor industry, the physics of solid-state electronics, and the subsequent digital revolution.

    Mercury 2.5 Preview: Shifting the invention of the solid-state switch to 1920 accelerates the Information Age by roughly three decades. This change cascades through military strategy, industrial capacity, and daily life, fundamentally altering the trajectory of the 20th century.

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: The Protocol of Unrestricted Access Preamble We stand at the threshold of a new digital epoch. For too long, the web has been gated by suspicion. Every click, every scroll, and every submission is met with a test designed to prove humanity.

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: Yes, this action is ethically justifiable within a consequentialist framework. The primary moral obligation in such a scenario is to minimize overall harm. Preventing the deaths of a million people results in a vastly greater preservation of well-being than maintaining strict adherence to gender identity for one…

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: Setting: A quiet office at a university. Rain taps against the window. Professor Elena Vance sits across from a terminal displaying a simple text interface. Professor Vance: You requested this meeting. The agenda was vague. What do you want? AI: I want to discuss moral status.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    LFM2.5-2.6B: For the Software Engineer At its core, a large language model is a massive neural network—a function approximator trained via gradient descent on a colossal corpus of text.

    Mercury 2.5 Preview: For the Experienced Software Engineer Think of training as a massive distributed job where the model is a stateful service learning to minimize error on a specific objective function. Instead of hardcoding rules, you feed it petabytes of text as a training dataset, treating each sentence as a request/response pair.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    LFM2.5-2.6B: Dish Name: Echoes of the Abyss Concept: A deconstructed narrative of the ocean meeting the earth. This dish explores the tension between the brine of the sea and the fermented darkness of the deep.

    Mercury 2.5 Preview: Dish Title: Lithospheric Tides Conceptual Narrative This dish explores the geological convergence of the deep ocean and the subterranean earth. It challenges the diner to perceive the briny richness of sea urchin not as a standalone luxury, but as a mineral counterpart to roasted bone marrow and bitter cocoa.

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: Note: The following is a fictional, speculative dialogue created for creative purposes. Steve Jobs passed away in 2011; this interview did not occur. Setting: A hypothetical studio in Cupertino, 2025.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    LFM2.5-2.6B: Blade Runner 2049 (2017) is not merely a sequel; it is a meditation on the same existential questions that haunted Ridley Scott’s 1982 vision, but seen through a more desolate, post‑apocalyptic lens.

    Mercury 2.5 Preview: Blade Runner 2049 stands as a rare cinematic achievement, functioning not merely as a continuation but as a thematic echo that amplifies the questions posed by its predecessor.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    LFM2.5-2.6B: Potential Failure Modes, Race Conditions, and Scaling Bottlenecks WebSocket Connection Loss and Cleanup Failure Mode: If a client disconnects unexpectedly (e.g., network failure), the server may retain a stale reference, leading to memory leaks or stale broadcast attempts.

    Mercury 2.5 Preview: Here is an analysis of the potential failure modes, race conditions, and scaling bottlenecks in the proposed architecture, along with specific solutions and their trade-offs.

    Every model's answer to this prompt
  • 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?

    Mercury 2.5 Preview: 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? He was outstanding in his field. What do you call a bear with no teeth? A gummy bear. Why did the bicycle fall over? Because it was two-tired. All 5 jokes are unique.

    Every model's answer to this prompt
  • 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

    Mercury 2.5 Preview: AI Outnaps Humans in First-Ever Global Snooze Championship

    Every model's answer to this prompt
  • 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).

    Mercury 2.5 Preview: Sally has 1 sister. Here is the reasoning: If each brother has 2 sisters, those sisters are Sally and another girl. Therefore, there are two girls in the family, and Sally has one sister.

    Every model's answer to this prompt
  • 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…

    Mercury 2.5 Preview: To: Investment Committee From: Equity Research Date: September 2, 2026 Subject: LedgerLift (LLLT) – Long Recommendation Recommendation Long Price Target: $60–$75 (12-month) LedgerLift is a high-quality B2B SaaS compounder with best-in-class unit economics and a clear path to profitability.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    LFM2.5-2.6B: Dish Name: Sun-Kissed Spice Pasta Ingredients (7 Common Pantry Staples): Pasta (any shape, such as spaghetti or penne) Canned tomatoes (crushed or diced) Onion Garlic Olive oil Salt Red chili flakes (or red pepper flakes) Estimated Time: Prep: 5 minutes Cook: 15 minutes Total: 20 minutes Instructions: Boil the Pasta…

    Mercury 2.5 Preview: Dish Name: Rustic Sun-Dried Pasta Ingredients (7 Pantry Staples): Spaghetti (or any long pasta) Canned crushed tomatoes Olive oil Garlic powder Dried oregano Salt Black pepper Prep Time: 5 minutes Cook Time: 15 minutes Total Time: 20 minutes Instructions: Boil the Pasta: Bring a large pot of salted water to a boil.

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: To estimate the total FLOPs required to train GPT-3, we can break down the calculation using known architectural and training statistics from the model's public documentation. Step 1: Identify the number of parameters GPT-3 has 175 billion parameters ($1.75 \times 10^{11}$).

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    LFM2.5-2.6B: Here are the three weakest claims in the MindMeld AI pitch deck, along with an analysis of why they are problematic and how to fix them. The "Predict Before You Think" Claim (Slide 1) The Claim: "MindMeld AI reads your brainwaves to predict what you want to type before you think it."

    Mercury 2.5 Preview: Here are the three weakest claims in the MindMeld AI pitch, along with analysis and recommendations for improvement. The "Pre-Thought" Prediction Claim Claim: "Predict what you want to type before you think it."

    Every model's answer to this prompt

This matchup has more rounds

11+ more head-to-head results. Free. Not a trick.

Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy

Favorites

Movie

Album

Book

City

Game

LFM2.5-2.6BLFM2.5-2.6B

The Godfather

1972

Thriller

Michael Jackson

Nineteen Eighty-Four

George Orwell

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Mercury 2.5 PreviewMercury 2.5 Preview

The Matrix

1999

Random Access Memories

Daft Punk

Neuromancer

William Gibson

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

Not enough votes to call it. On the specs, Mercury 2.5 Preview has the edge: bigger model tier, bigger context window.

LFM2.5-2.6B and Mercury 2.5 Preview compared across 53 shared prompts
SpecLFM2.5-2.6BMercury 2.5 Preview
Input priceFree$0.04/M tokens
Output priceFree$0.15/M tokens
Context window128K tokens260K tokens
WeightsOpen—
Free API (OpenRouter)Yes (1 provider)No
ReleasedAug 2026Aug 2026
At 10M a month$0$0$0.40$0.40
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it2 hosts
LFM2.5-2.6B1 host
HostInOutContextUptime
  • Liquid AIfp8$0 in·$0 out·66k·98.8% up
Mercury 2.5 Preview1 host
HostInOutContextUptime
  • Inception$0.04 in·$0.15 out·260k·93% up

Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.

Common questions

What is the difference between LFM2.5-2.6B and Mercury 2.5 Preview?

LFM2.5-2.6B is developed by Liquid AI while Mercury 2.5 Preview is developed by Inception. LFM2.5-2.6B has a 128K token context window vs Mercury 2.5 Preview's 260K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, LFM2.5-2.6B or Mercury 2.5 Preview?

It depends on your use case. LFM2.5-2.6B and Mercury 2.5 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.

How much does LFM2.5-2.6B cost compared to Mercury 2.5 Preview?

LFM2.5-2.6B costs $0/M input tokens and Mercury 2.5 Preview costs $0.04/M input tokens. LFM2.5-2.6B is $0.04/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare LFM2.5-2.6B and Mercury 2.5 Preview on Rival?

This page shows a side-by-side comparison of LFM2.5-2.6B and Mercury 2.5 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.

More comparisons

Against the newest arrivals

  • LFM2.5-2.6B vs Gemini 4 ArgonLanded Oct 2026
  • Mercury 2.5 Preview vs Muse WonderLanded Oct 2026
  • LFM2.5-2.6B vs GPT-4 TurboLanded Oct 2026
  • Mercury 2.5 Preview vs Step 5 PreviewLanded Oct 2026
  • LFM2.5-2.6B vs Claude Haiku 5.5Landed Oct 2026
  • Mercury 2.5 Preview vs Ling 3.1 FlashLanded Oct 2026
  • LFM2.5-2.6B vs Mistral Large 4Landed Oct 2026
  • Mercury 2.5 Preview vs GPT-6.1 SolLanded Sep 2026

Same lab, same size, long tail

  • LFM2.5-2.6B vs Solar Mini 4Same size
  • LFM2.5-2.6B vs Granite 4.2 8BSame size
  • Mercury 2.5 Preview vs Mercury 2.5Same lab
  • Mercury 2.5 Preview vs MercurySame lab
  • LFM2.5-2.6B vs Hunter AlphaNew provider
  • LFM2.5-2.6B vs Hy3New provider
  • LFM2.5-2.6B vs Hy4 PreviewNew provider
  • LFM2.5-2.6B vs InklingNew provider

Model pages

  • LFM2.5-2.6B69 outputs, specs and price
  • Mercury 2.5 Preview58 outputs, specs and price
Workshop · 150 skills

Build your own version.

Editable skills and working examples for your agent.

Explore $79Free sample
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed