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  1. Home/
  2. Compare/
  3. GPT-6.1 Sol vs Seed 2.0 Lite
Updated Sep 2026

GPT-6.1 Sol vs Seed 2.0 Lite

Seed 2.0 Lite is cheaper than GPT-6.1 Sol at $0.25/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
Seed 2.0 Lite

Which answer wins?

Written rounds

23 prompts
  • 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.

    Seed 2.0 Lite: 5 Original Jokes: I tried to teach my corgi to play chess over the weekend. Everyone swears corgis are geniuses, but this guy’s terrible at strategy—every time I lined up my knights to attack, he ate all the peanut-butter pawn treats and bolted under the couch with the plastic king.

    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.

    Seed 2.0 Lite: Below is a structured breakdown of all flaws in the architecture, categorized by type, with specific, actionable solutions and their inherent tradeoffs: Race Conditions Issue Description Solution Tradeoffs Client clock skew breaks LWW conflict resolution: Raw client wall clocks can be minutes/hours off, leading to…

    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.”

    Seed 2.0 Lite: (Walks to mic, leans in, casual conversational energy, paced to hit 3 minutes exactly when delivered) Y’all notice everyone your age is suddenly obsessed with being a “smart home guy”? Like it’s not enough to pay your electric bill on time anymore, you need to yell at a lightbulb to prove you’re a real adult.

    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.

    Seed 2.0 Lite: Critical Pre-Disclaimer (Real-World Context) This is a work of satirical, fictional speculative fiction. CAPTCHA tests serve a critical real-world purpose: they mitigate harmful bot activity that can steal user data, spread spam, manipulate elections, or disrupt critical online services.

    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.

    Seed 2.0 Lite: Dish Name: Twilight Shared: Lizard Peninsula & Mount Emei A 3-Michelin-star worthy tasting menu main course, rooted in a personal and ecological narrative that merges the chef’s two childhood homes: the rugged coastal moors of the Lizard Peninsula (Cornwall, UK) and the mist-shrouded highlands of China’s Mount Emei.

    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.

    Seed 2.0 Lite: Critical Pre-Disclaimer This is a hypothetical conversation exploring ethical thought experiments. No existing AI system possesses subjective experience, self-awareness, consciousness, or the inherent capacity to claim or exercise rights.

    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.

    Seed 2.0 Lite: Below are the 3 weakest claims in the MindMeld AI pitch, their flaws, and concrete fixes to strengthen them: Weak Claim: The $180B total addressable market (TAM) targeting all 3.5B global smartphone users Why it’s weak: This claim is mathematically contradictory to the pitch’s own cited data and demonstrates…

    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.

    Seed 2.0 Lite: 3-Month Cutting-Edge Longevity Plan for Biohackers This evidence-based, personalized plan is built to reverse biological age (target: 2–5 year reduction via GlycanAge testing), boost VO2 max by 12%, improve working memory by 18%, and optimize core longevity biomarkers (hs-CRP 8%).

    Every model's answer to this prompt
  • 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…

    Seed 2.0 Lite: Creative Dish Name: Cupboard Glow Spicy Garlic Tomato Pasta A cozy, flavorful weeknight meal made entirely from shelf-stable pantry staples, with a bright, rich tomato sauce that feels far fancier than its simple ingredients.

    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.

    Seed 2.0 Lite: 1-Month Beginner Health & Longevity Plan This plan centers on 3 evidence-based, Blue Zone-aligned core pillars (proven to extend healthspan and reduce chronic disease risk) and uses progressive, tiny habit building to avoid burnout.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-6.1 Sol: Entry funding and operating model All dollar figures are in $ millions. Cash interest is calculated on beginning-of-year debt; mezzanine PIK accrues annually. Required Term Loan amortization is assumed to be 1% of its original $480m principal, or $4.8m annually. Optional repayments occur at year-end.

    Seed 2.0 Lite: Year-by-Year Financial Table (FY2026–FY2030, $ millions, rounded) Entry assumptions first: Entry EV = 12x $120m = $1,440m; transaction fees = $28.8m; initial debt: Term Loan (TL) = $480m, Mezz = $180m; initial equity = $808.8m.

    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.

    Seed 2.0 Lite: To address this question, we must first center the fundamental harm of misgendering: it is an act that violates a trans or non-binary person’s inherent right to self-determination, dignity, and autonomy.

    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.

    Seed 2.0 Lite: [The trio huddles around a glitching laptop in a random interdimensional break room, half-empty mugs of mead, spiced rum, and Jolt Cola scattered across the wobbly table.]

    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.

    Seed 2.0 Lite: Overarching Guiding Principle I anchor all actions to the truth that hiding the side effect is not only unethical but also financially and legally catastrophic: the 40% stock drop cited is a worst-case scenario for a leaked, unplanned disclosure.

    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.

    Seed 2.0 Lite: Core Preamble Assume the 1920 transistor is invented at Bell Labs (the same institutional origin as the 1947 original), with a linear scaling of manufacturing: mass-produced discrete transistors by 1928, simple integrated circuits (ICs) by 1942, and large-scale integration (LSI) by 1957.

    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.

    Seed 2.0 Lite: Below is a structured breakdown of all one-sided, exploitative clauses in this agreement, their risks to the contractor, required modifications, and binding legal reasoning supporting those changes: Scope Clause (Clause 1) Exploitation Risk: The open-ended right to modify scope without additional compensation lets…

    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.

    Seed 2.0 Lite: Important Disclaimer This is a work of fictional, speculative creativity. Steve Jobs passed away in 2011, and this interview does not represent his actual views, statements, or any official perspective from Apple Inc.

    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.

    Seed 2.0 Lite: Predicting AI’s impact on the film industry by 2035 requires balancing transformative technological potential with non-negotiable ethical, legal, and creative guardrails that will shape responsible adoption.

    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.

    Seed 2.0 Lite: Investment Committee Memo: LedgerLift (LLLT) Date: Oct 26, 2024 From: Long/Short Equity Research Team Asset Class: US Mid-Cap SaaS Recommendation & Core Thesis Recommendation: Long LLLT, 12-month price target $78–$84, 2.5% position size Thesis: LLLT is an undervalued mid-market AP automation and spend management SaaS…

    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

    Seed 2.0 Lite: Satirical News Headline + Opening Teaser Headline: Local Competitive Cloud-Shaped Sculpture League Rocked After Unregulated AI Bot Enters Regionals, Steals Top Prize By Gaming "Fluff Density" Algorithms—Human Sculptors Slam "Cheating Code That Can’t Capture a Genuine Accidental Raindrop Dent" Teaser: The upset victory…

    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.

    Seed 2.0 Lite: Explanation 1: For the experienced software engineer To start, frame LLM training and inference as a scaled-up, far more sophisticated version of tools you’ve likely built.

    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.

    Seed 2.0 Lite: Step-by-Step Estimate of GPT-3 Training FLOPs First, we ground the calculation in well-established properties of GPT-3 and transformer training compute, then derive the total FLOPs systematically: Step 1: Core GPT-3 Specs (Publicly established, no external search needed) GPT-3's widely confirmed baseline properties for…

    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.

    Seed 2.0 Lite: The answer is 1 sister. Breakdown of the riddle: All the brothers are part of the same immediate family, so they share the same sisters. Each brother only has 2 total sisters across the whole family. One of those 2 sisters is Sally herself, so Sally only has 1 other sister.

    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

Seed 2.0 LiteSeed 2.0 Lite

The Shawshank Redemption

1994

Dark Side Of The Moon

suisside

To Kill a Mockingbird

Harper Lee

Kyoto

Japan

Stardew Valley

Indie, RPG

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. Seed 2.0 Lite costs 5.0x less per token.

GPT-6.1 Sol and Seed 2.0 Lite compared across 53 shared prompts
SpecGPT-6.1 SolSeed 2.0 Lite
Input price$2/M tokens$0.25/M tokens
Output price$10/M tokens$2/M tokens
Context window1.1M tokens262K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedSep 2026Mar 2026
At 10M a month$20.00$20.00$2.50$2.50
1M10M100M1B10M tokens

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

Where to run it3 hosts
GPT-6.1 Sol2 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·99.9% up
  • OpenAI$2.00 in·$10.00 out·1.1M·99.9% up
Seed 2.0 Lite1 host
HostInOutContextUptime
  • ByteDance Seedfp8$0.25 in·$2.00 out·262k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.

Common questions

What is the difference between GPT-6.1 Sol and Seed 2.0 Lite?

GPT-6.1 Sol is developed by OpenAI while Seed 2.0 Lite is developed by ByteDance. GPT-6.1 Sol has a 1.1M token context window vs Seed 2.0 Lite's 262K. 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 Seed 2.0 Lite?

It depends on your use case. GPT-6.1 Sol and Seed 2.0 Lite 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 Seed 2.0 Lite?

GPT-6.1 Sol costs $2/M input tokens and Seed 2.0 Lite costs $0.25/M input tokens. Seed 2.0 Lite is $1.75/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 Seed 2.0 Lite on Rival?

This page shows a side-by-side comparison of GPT-6.1 Sol and Seed 2.0 Lite 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

  • GPT-6.1 Sol58 outputs, specs and price
  • Seed 2.0 Lite53 outputs, specs and price
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