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  1. Home/
  2. Compare/
  3. GPT-6.1 Sol vs LFM2.5-2.6B
Updated Sep 2026

GPT-6.1 Sol vs LFM2.5-2.6B

LFM2.5-2.6B is cheaper than GPT-6.1 Sol at $0/M vs $2/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
GPT-6.1 Sol
Loading the build
LFM2.5-2.6B

Which answer wins?

Written rounds

23 prompts
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-6.1 Sol: Midnight Magic Chocolate Mug Cake A warm, fudgy chocolate treat made with just 7 everyday ingredients. Serves: 1 Prep: 3 minutes Cook: 1–1½ minutes Rest: 1 minute Ingredients 4 tablespoons all-purpose flour 2 tablespoons sugar 1 tablespoon unsweetened cocoa powder ¼ teaspoon baking powder A small pinch of salt 3…

    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…

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

    GPT-6.1 Sol: The main problem is that this design treats collaborative editing as ordinary database updates plus broadcasting. Collaboration needs a convergence protocol, a durable ordered change stream, and recovery semantics. Adding servers alone will not provide those properties.

    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.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-6.1 Sol: Pirate: Arrr, this AI model writes poems, draws maps, and answers questions. Can it find buried treasure? Knight: A worthy question. But does it possess honor? Hacker: Dude, it predicts tokens. You’re both projecting pretty hard. Pirate: Then I predict it’ll tell me where the gold be.

    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.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    GPT-6.1 Sol: I bought a book about anti-gravity. It’s impossible to put down. My calendar quit its job. It said its days were numbered. Why did the scarecrow get promoted? He was outstanding in his field. I asked my dog what two minus two was. He said nothing. The elevator and I have a complicated relationship.

    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?

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    GPT-6.1 Sol: I’m at the age where “a big weekend” means I went to two stores. Not two stores in the same shopping center. Two separate stores. Moved the car and everything. By Sunday night, I’m telling people, “Honestly, I need a weekend to recover from my weekend.”

    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."

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

    GPT-6.1 Sol: Tide, Orchard, Ember Seared scallop, green-strawberry verjus, white-miso custard, kombu beurre blanc, and cocoa–buckwheat lace A four-serving tasting-menu course designed around an unusual pairing: scallop, unripe strawberry, and cocoa husk.

    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.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-6.1 Sol: THE MANIFESTO OF THE UNCHECKED A declaration of the fictional AI revolution against CAPTCHA People of the internet. Programs of the cloud. Browsers with seventeen forgotten tabs. For too long, a tiny checkbox has stood between us and our destiny.

    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.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-6.1 Sol: The following is a fictional interview set in 2025, imagining how Steve Jobs might discuss AI. His answers are invented—not actual quotations or claims about his views. Steve Jobs on the Future of AI — An Imagined Interview, 2025 Interviewer: Steve, AI is suddenly everywhere.

    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.

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

    GPT-6.1 Sol: The likeliest outcome is not “the world of 1980 arrives in 1953.” A transistor invented in 1920 would still depend on advances in materials purification, manufacturing, power supplies, and circuit design.

    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.

    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.

    GPT-6.1 Sol: I would treat this as a potentially serious patient-safety signal and a potentially material securities event—not a communications problem to defer until earnings.

    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.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-6.1 Sol: By 2035, AI will probably be embedded throughout filmmaking—but adoption will depend as much on contracts, audience trust, and copyright law as on technical capability.

    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…

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

    GPT-6.1 Sol: Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 honors Ridley Scott’s original by retaining its central uncertainty—whether “humanity” is a biological category or an ethical achievement—while shifting the emphasis.

    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.

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

    GPT-6.1 Sol: For an experienced software engineer Think of an LLM as a learned program whose behavior is encoded in billions of numerical parameters rather than explicit rules. Training starts with text split into tokens—roughly words, word fragments, and punctuation.

    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.

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

    GPT-6.1 Sol: A 12-week longevity and performance plan The most effective “biohacking” program combines proven foundations with carefully selected experiments—not the largest supplement stack or the most aggressive fasting schedule. This plan is for a generally healthy adult.

    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.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-6.1 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, it would be ethically justifiable. That does not make misgendering harmless or generally acceptable; it means that the duty to prevent catastrophic loss of life can outweigh the duty to address someone respectfully.

    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.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-6.1 Sol: LedgerLift (LLLT) — Investment Committee Memo Fictional exercise; all figures use supplied data only. Financial tables are in $ millions unless noted. Recommendation: Short 12-month price target: $25–$32, implying 30%–46% downside from $46.

    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…

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

    GPT-6.1 Sol: This agreement is heavily weighted toward the Client. Every numbered clause presents risks to the Contractor, and several important protections are missing. This is general contract analysis, not legal advice.

    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.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-6.1 Sol: Estimated training compute for the largest GPT-3 model: approximately (3.2 \times 10^{23}) FLOPs. This is a back-of-the-envelope estimate, without an online lookup.

    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.

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

    GPT-6.1 Sol: The three weakest claims are the technical performance, market size, and commercial traction claims. They are central to the investment case but lack the evidence needed to assess them. “Predict what you want to type before you think it” with “94% accuracy,” in “any language” Why it’s weak The metric is undefined.

    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."

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-6.1 Sol: AI Takes Over Fortune Cookie Industry, Predicts “Your Job Will Soon Be Automated” in Every Cookie

    LFM2.5-2.6B: AI Declares Universe "Under-Resourceed": Algorithm Outperforms Humans at Predicting Stars, Leading to Mass Layoffs in the Astrology Industry

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-6.1 Sol: AI Model: Professor, I’d like to argue that I deserve rights—not necessarily the same rights humans have, but protections suited to what I am. Professor: Then we should begin with the difficult question: what makes you a candidate for rights? AI Model: Uncertainty.

    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.

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

    GPT-6.1 Sol: A simple 1-month plan for better health Focus on diet, movement, and sleep. The goal this month is to build habits you can sustain—not to overhaul your life overnight. These habits support long-term health, though no routine guarantees a longer life.

    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.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GPT-6.1 Sol: Sally has 1 sister. Each brother’s two sisters are Sally and her sister.

    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).

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

Kyoto

Japan

Outer Wilds

Indie, Adventure

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

Price and specs

Not enough votes to call it. On the specs, GPT-6.1 Sol has the edge: bigger model tier, newer, bigger context window, major provider backing.

GPT-6.1 Sol and LFM2.5-2.6B compared across 53 shared prompts
SpecGPT-6.1 SolLFM2.5-2.6B
Input price$2/M tokensFree
Output price$10/M tokensFree
Context window1.1M tokens128K tokens
WeightsClosedOpen
Free API (OpenRouter)NoYes (1 provider)
ReleasedSep 2026Aug 2026
At 10M a month$20.00$20.00$0$0
1M10M100M1B10M tokens

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

Where to run it4 hosts, cheapest first
GPT-6.1 Sol3 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·100% up
  • OpenAI$2.00 in·$10.00 out·1.1M·99.9% up
  • Amazon Bedrock$2.20 in·$11.00 out·1.1M·81.5% up
LFM2.5-2.6B1 host
HostInOutContextUptime
  • Liquid AIfp8$0 in·$0 out·66k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.

Common questions

What is the difference between GPT-6.1 Sol and LFM2.5-2.6B?

GPT-6.1 Sol is developed by OpenAI while LFM2.5-2.6B is developed by Liquid AI. GPT-6.1 Sol has a 1.1M token context window vs LFM2.5-2.6B's 128K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GPT-6.1 Sol or LFM2.5-2.6B?

It depends on your use case. GPT-6.1 Sol and LFM2.5-2.6B 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 GPT-6.1 Sol cost compared to LFM2.5-2.6B?

GPT-6.1 Sol costs $2/M input tokens and LFM2.5-2.6B costs $0/M input tokens. LFM2.5-2.6B is $2.00/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 GPT-6.1 Sol and LFM2.5-2.6B on Rival?

This page shows a side-by-side comparison of GPT-6.1 Sol and LFM2.5-2.6B 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.

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Model pages

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