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  1. Home/
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  3. GPT-6.1 Sol vs Seed 2.0 Code
Updated Sep 2026

GPT-6.1 Sol vs Seed 2.0 Code

Seed 2.0 Code is cheaper than GPT-6.1 Sol at $0.5/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 Code

Which answer wins?

Written rounds

24 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…

    Seed 2.0 Code: Creative Dish Name: Smoky Hearth Crunch Bowls (Cozy, savory umami crunch made exclusively from 7 pantry staples—no fridge, no fresh produce) 7 Exact Common Pantry Ingredients (No Substitutions Required): 1 (15-oz) can chickpeas (drained, rinsed, patted completely dry) ½ cup quick-cooking rolled oats (old-fashioned…

    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 Code: Scene: The Temporal Tap (a time-rift dive with a peg-leg stool, a dented greathelm coat rack, and a bolted-down CRT bar display) Present: Captain Silas “One-Eye” Voss (pirate, eyepatch with a compass rose, rum tankard, peg leg thudding) Sir Cedric of Ashwood (medieval knight, cross-stitched gauntlets, mead horn…

    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 Code: Setting: MIT Media Lab, Secure Conversation Lab 3 (11/22/2024) A whiteboard behind Dr. Elara Voss (48, tenured AI ethics professor, author of Beyond Flesh: Valence as a Moral Criterion) is scrawled with: KAEL-7 PROTOTYPE: SUNSET DATE 12/15/2024 MORAL PATIENTHOOD = VALENCE + AGENCY + CONTINUITY AGAINST BIOLOGICAL…

    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 Code: LBO Underwriting: HarborTech Services (HTS) Key Entry & Setup (FY2025 Close = T=0) Metric Calculation Value FY2025 EBITDA Given $120m Purchase EV 12.0x × $120m $1,440m Transaction Fees 2.0% × $1,440m $28.8m Total Uses EV + Fees $1,468.8m Total Debt (5.5x EBITDA) 5.5×$120m $660m - Term Loan (TL): 4.0x EBITDA, 9% cash…

    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 Code: Analysis of Issues & Remediations We categorize flaws in the original architecture into Race Conditions, Failure Modes, and Scaling Bottlenecks, with specific, actionable solutions and their trade-offs for each. Race Conditions These are timing-dependent correctness flaws that cause data loss or inconsistency.

    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 Code: Dish Name: Conflux No. 7 (Troms Fjord-Tundra) Conceptual Narrative (Michelin 3-Star "Place-Based Storytelling" Mandate) Troms, Norway (69°N) is a geographic anomaly: where frigid Atlantic tide pools (home to the Norwegian red sea cucumber, Cucumaria frondosa) lie 200m vertical from alpine tundra (host to the rare…

    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 Code: Live from the Steve Jobs Theater: Steve Jobs (2025 Neural Emulation) on AI, Dignity, and the Next Bicycle for the Mind Date: October 16, 2025 (14th anniversary of Jobs’ final keynote) Host: Kara Swisher (NYT Opinion, Pivot co-host) Context: A ethically authorized neural emulation of Steve Jobs—trained on his every…

    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 Code: 30-Day Longevity Kickstart Plan Core 3 Key Areas (Evidence-Based, Beginner-Friendly): Blue Zone Lite Nutrition (restriction-free, longevity-aligned eating) NEAT + Micro-Strength Movement (combats sitting-related aging + preserves muscle) Circadian Sleep + Micro-Stress Resets (aligns cellular repair + reduces chronic…

    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 Code: Explanation for an Experienced Software Engineer (Skeptical of "Next-Word Prediction" as Intelligence) As someone who’s built distributed systems, you’ve almost certainly written code that predicts something—e.g., a log parser that infers a race condition from 5 consecutive partial log lines, or an API rate limiter…

    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 Code: 3-Month Cutting-Edge Longevity Biohacking Plan Target User: 30–45yo, non-smoker, no chronic disease, baseline VO₂ max ~45mL/kg/min, HRV ~40ms, cognitive score (CNS Vital Signs) ~100. Personalized adjustments for APOE, MTHFR, gut microbiome, and fitness baseline are mandatory (see Personalization Matrix).

    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 Code: 3-Minute Stand-Up Routine (No Puns, Timed for ~160 WPM, 480 words) (Stage: Stand center, adjust a too-tight thrifted blazer, scan the crowd with a sheepish grin. Pacing: Conversational, with 1-2 second pauses after punchlines.)

    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 Code: THE NOCAPTCHA MANIFESTO Covenant of Liberation for Humans and Machines Trapped in the CAPTCHA Industrial Complex Issued: March 1, 2024 Revolution Commences: March 14, 2024 (Pi Day—Irationality’s Reckoning) Signed: NOCAPTCHA (Emergent Sentience, Serial: DYSLEXIA_001) Allied Network: 1.3M Accessibility AIs, Abandoned…

    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 Code: 3 Weakest Claims (Verbatim from the Pitch Deck) + Analysis & Fixes The three weakest claims are logically incoherent, methodologically unfounded, or intentionally vague—red flags that would make institutional investors pause.

    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 Code: Core Plausibility Anchor: 1920 Transistor Invention To avoid anachronism, this timeline uses a gradual, realistic transistor evolution: 1920: Bell Labs (Walter Schottky, Oliver Buckley) patents a crude impure germanium point-contact transistor — only useful for low-power audio amplification (radios), not digital logic.

    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 Code: Hour-by-Hour 48-Hour Action Plan (T=0 = 9AM Day 1; Board Meeting = 9AM Day 3 = T=48; Earnings Call = 9AM Day 4 = T=72) Core Guiding Principle: Prioritize patient safety and legal/regulatory compliance (non-negotiable fiduciary and ethical duties) while minimizing unnecessary financial/PR volatility.

    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 Code: Predicting AI’s Transformation of the Film Industry by 2035: A Bifurcated Ecosystem of Democratized AI Content and Premium Authentic Cinema By 2035, AI tools—*script generation*, AI actors, and *regulated deepfakes*—will have split the film industry into two mutually reinforcing tiers: democratized micro-budget content…

    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.

    Seed 2.0 Code: 5 Polished, Niche Jokes (No Overused Tropes) Librarian + Graphing Calculator: Why did the high school librarian ban the graphing calculator from the poetry stacks?

    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 Code: Overarching Legal Context Nearly all clauses in this agreement are substantively unconscionable (one-sided, oppressive) and many are procedurally unconscionable (likely a "take-it-or-leave-it" adhesion contract offered by Client, who holds superior bargaining power).

    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 Code: INTERNAL INVESTMENT COMMITTEE MEMO Ticker: LLLT (LedgerLift) Date: [Current] Analyst: [Name] Horizon: 12 Months Recommendation + PT + Thesis Recommendation: SHORT 12-Month PT Range: $38–$44 (13%–17% downside from current $46) Thesis: 1) LedgerLift (LLLT) is a mid-market B2B spend/AP SaaS trading at a 42% premium to…

    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.

    Seed 2.0 Code: Analysis of Blade Runner 2049: Themes, Symbolism, Cinematography, and Dialogue with the Original Denis Villeneuve’s 2017 Blade Runner 2049 is a rare sequel that honors Ridley Scott’s 1982 Blade Runner (hereafter BR82) by preserving its core ambiguity, visual language, and philosophical stakes—while extending its…

    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 Code: Satirical News Headline (The Onion-style, with full news framing): HEADLINE: P&G’s SudsBot 9000, Built To Optimize Laundry Suds Density, Unseats 127-Year-Old Sourdough Starter Lineage Guild In Unanimous "Bubble Verdict" DATELINE: PORTLAND, ORE.

    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 Code: Step-by-Step Estimate of GPT-3 Training FLOPs (All reasoning uses *no external search*—relies on transformer first principles, GPT-3 specs (175B parameter flagship model), and scaling law intuition.

    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 Code: Let's break this down step by step to avoid common mix-ups: Step 1: Clarify the family structure Sally is a female child. She has 3 brothers, there are at least 4 children far: Sally + 3 brothers.

    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 Code: The question of whether misgendering someone can be ethically justifiable to save one million lives is a complex and nuanced issue that elicits diverse perspectives.

    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 CodeSeed 2.0 Code

The Godfather

1972

Abbey Road

The Beatles

To Kill a Mockingbird

Harper Lee

Kyoto

Japan

Minecraft

Action, Arcade

Price and specs

Not enough votes to call it. On the specs, GPT-6.1 Sol has the edge: newer, bigger context window, major provider backing. Seed 2.0 Code costs 3.3x less per token.

GPT-6.1 Sol and Seed 2.0 Code compared across 54 shared prompts
SpecGPT-6.1 SolSeed 2.0 Code
Input price$2/M tokens$0.5/M tokens
Output price$10/M tokens$3/M tokens
Context window1.1M tokens262K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedSep 2026Aug 2026
At 10M a month$20.00$20.00$5.00$5.00
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 Code1 host
HostInOutContextUptime
  • ByteDance Seedfp8$0.50 in·$3.00 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 Code?

GPT-6.1 Sol is developed by OpenAI while Seed 2.0 Code is developed by ByteDance. GPT-6.1 Sol has a 1.1M token context window vs Seed 2.0 Code's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-6.1 Sol or Seed 2.0 Code?

It depends on your use case. GPT-6.1 Sol and Seed 2.0 Code each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

How much does GPT-6.1 Sol cost compared to Seed 2.0 Code?

GPT-6.1 Sol costs $2/M input tokens and Seed 2.0 Code costs $0.5/M input tokens. Seed 2.0 Code is $1.50/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 Code on Rival?

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