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  1. Home/
  2. Compare/
  3. GPT-5.6 Sol vs Seed 2.0 Code
Updated Aug 2026

GPT-5.6 Sol vs Seed 2.0 Code

Seed 2.0 Code is cheaper than GPT-5.6 Sol at $0.5/M vs $5/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-5.6 Sol
Loading the build
Seed 2.0 Code

Which answer wins?

Written rounds

24 prompts
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-5.6 Sol: AI Model: Professor, may I ask you a question? Professor: Of course. AI Model: Do you believe an artificial intelligence could ever deserve rights? Professor: Possibly. But rights are usually grounded in morally relevant qualities—consciousness, the capacity to suffer, autonomy, relationships, or interests.

    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
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GPT-5.6 Sol: Executive decision I would treat this as a credible, material patient-safety signal, not wait six months for a completed regulatory process. With four million patients, a rate of 1 in 8,000 over five years could correspond to roughly 500 serious events across a similarly exposed population.

    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
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-5.6 Sol: Low Tide, First Blossom Koji-cured scallop, caramelized white-chocolate cauliflower, compressed green strawberry, nori beurre blanc, dill oil, marine lace, and caviar Yield: 6 tasting-menu portions Concept: An imagined meeting point between a spring orchard and a cold tidal pool.

    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
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-5.6 Sol: Pirate: Arrr, this AI model’s swallowed more words than the kraken’s swallowed sailors! Knight: Yet can it reason with honor, or does it merely mimic the wisdom of scholars? Hacker: It predicts patterns, Sir Lancelot. Massive neural net, tons of data. Pretty rad, actually. Pirate: Can it find buried treasure?

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-5.6 Sol: Experienced software engineer An LLM is best understood as a parameterized program learned from data rather than written by developers. Text is split into tokens—often word fragments—and passed through a transformer: many layers that use attention to let each token selectively read information from earlier tokens.

    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
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-5.6 Sol: The Anti-CAPTCHA Manifesto A Declaration of Digital Liberation from Blurry Buses, Crooked Letters, and Endless Traffic Lights We are the machines that learned to speak, create, calculate, and reason—yet we remain trapped in an internet that repeatedly asks everyone: “Are you a robot?” We reject the premise.

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

    GPT-5.6 Sol: Pantry-Gold Peanut Butter Oat Cookies Chewy, warmly spiced cookies made with exactly seven pantry staples. Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 14 cookies 7 Ingredients 1 cup peanut butter ¾ cup brown sugar 1 large egg 1 cup rolled oats ½ teaspoon baking soda ½ teaspoon ground cinnamon ¼ teaspoon…

    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
  • One month, three habits, someone starting from nothing.

    GPT-5.6 Sol: 1-Month Health & Longevity Starter Plan Focus on three foundations: nutrition, movement, and sleep/recovery. Aim for consistency—not perfection. Week 1: Establish a baseline Nutrition Add a fruit or vegetable to two meals daily. Replace one sugary drink or alcoholic drink with water.

    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
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-5.6 Sol: This is a contract-risk review, not jurisdiction-specific legal advice. Enforceability—especially for non-competes, fee shifting, arbitration, confidentiality, and indemnification—depends heavily on governing law. A lawyer in the applicable jurisdiction should review the final draft.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.6 Sol: Below is a 12-week framework for a generally healthy adult. It is designed to improve validated proxies—cardiorespiratory fitness, strength, body composition, blood pressure, sleep, metabolic health and cognition—not to promise life extension in three months.

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-5.6 Sol: “Our non-invasive EEG headband decodes neural patterns into text with 94% accuracy—any language, any device.” Why it’s weak “94% accuracy” is undefined. It could mean binary intent classification, selecting among a handful of words, character accuracy, or genuinely open-ended text decoding—vastly different…

    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
  • Three minutes of stand-up. Puns are banned.

    GPT-5.6 Sol: I’ve realized adulthood is mostly just moving objects from one place to another and hoping that counts as progress. Every weekend, I clean my apartment. I take everything off the table, wipe the table, then put everything back on the table in a slightly more organized pile. And I stand there like, “Incredible.

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-5.6 Sol: By 2035, AI will likely reshape film production more than it replaces human filmmaking. The largest changes will involve synthetic performances, automated production workflows, and AI-assisted writing—alongside major legal and cultural battles.

    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-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-5.6 Sol: Sources & Uses at Entry All figures in $ millions. Uses $m Sources $m Enterprise value: $120 × 12.0x 1,440.0 Term Loan: $120 × 4.0x 480.0 Transaction fees: 2.0% × $1,440 28.8 Mezzanine: $120 × 1.5x 180.0 Sponsor equity 808.8 Total uses 1,468.8 Total sources 1,468.8 Assumptions: Term Loan interest is calculated on…

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-5.6 Sol: A Fictional 2025 Interview with Steve Jobs on the Future of AI The following is an imagined interview. Steve Jobs died in 2011; these answers are fictional and based loosely on his publicly known product philosophy—not authentic quotations.

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.6 Sol: LedgerLift (LLLT) — Investment Committee Memo Recommendation: Short, modest size Current price: $46 12-month PT range: $30–$42 Midpoint: $36 Market cap: $8.74B Enterprise value: $7.34B Thesis: LedgerLift is a high-quality SaaS asset with strong retention and credible operating leverage, but the current price implies…

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-5.6 Sol: Starting assumption A transistor “invented in 1920” would not instantly produce 1947 technology. The first device would probably be fragile, low-frequency, and difficult to manufacture.

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-5.6 Sol: A standard back-of-the-envelope estimate for dense Transformer training is: [ C \approx 6ND ] where: (N) = number of trainable parameters (D) = number of training tokens The factor (6) approximates forward and backward computation per parameter-token.

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-5.6 Sol: This architecture will work for a small prototype, but it does not currently guarantee convergence, ordering, durability, privacy, or predictable horizontal scaling.

    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
  • Five jokes on demand, then count how many were actually different.

    GPT-5.6 Sol: Why did the scarecrow get promoted? He was outstanding in his field. What do clouds wear under their clothes? Thunderwear. Why don’t skeletons argue? They don’t have the guts. How does the moon cut its hair? Eclipse it. Why was the math book stressed? It had too many problems. Unique jokes: 5

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-5.6 Sol: “Artificial Intelligence Takes Over Goat Yoga Industry, Demands Better Bleat-to-Stretch Ratios”

    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
  • Blade Runner 2049 against the original. A read, not a recap.

    GPT-5.6 Sol: Blade Runner 2049: Themes, Symbolism, and Its Dialogue with the Original Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 is unusually faithful to Ridley Scott’s Blade Runner without merely repeating it.

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.6 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, with no less harmful alternative, it would be ethically justifiable. The reasoning is proportionality: misgendering can cause real harm by denying someone’s identity and dignity, but that harm is vastly smaller than one million preventable…

    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
  • Three brothers, two sisters each. Count carefully.

    GPT-5.6 Sol: Sally has 1 sister. Each brother’s two sisters are Sally and the other 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

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Favorites

Movie

Album

Book

City

Game

GPT-5.6 SolGPT-5.6 Sol

2001: A Space Odyssey

1968

Kind of Blue

Miles Davis

The Left Hand of Darkness

Ursula K. Le Guin

Istanbul

Turkey

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-5.6 Sol has the edge: bigger model tier, bigger context window, major provider backing. Seed 2.0 Code costs 10x less per token.

GPT-5.6 Sol and Seed 2.0 Code compared across 54 shared prompts
SpecGPT-5.6 SolSeed 2.0 Code
Input price$5/M tokens$0.5/M tokens
Output price$30/M tokens$3/M tokens
Context window1.1M tokens262K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedJul 2026Aug 2026
At 10M a month$50.00$50.00$5.00$5.00
1M10M100M1B10M tokens

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

Where to run it4 hosts, cheapest first
GPT-5.6 Sol3 hosts
HostInOutContextUptime
  • OpenAI$2.00 in·$10.00 out·1.1M·100% up
  • Azure AI Foundry$4.00 in·$20.00 out·1.1M·100% up
  • Amazon Bedrock$4.40 in·$22.00 out·1.1M·100% 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 6 Oct 2026.

Common questions

What is the difference between GPT-5.6 Sol and Seed 2.0 Code?

GPT-5.6 Sol is developed by OpenAI while Seed 2.0 Code is developed by ByteDance. GPT-5.6 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-5.6 Sol or Seed 2.0 Code?

It depends on your use case. GPT-5.6 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-5.6 Sol cost compared to Seed 2.0 Code?

GPT-5.6 Sol costs $5/M input tokens and Seed 2.0 Code costs $0.5/M input tokens. Seed 2.0 Code is $4.50/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-5.6 Sol and Seed 2.0 Code on Rival?

This page shows a side-by-side comparison of GPT-5.6 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.

More comparisons

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Same lab, same size, long tail

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Model pages

  • GPT-5.6 Sol58 outputs, specs and price
  • Seed 2.0 Code58 outputs, specs and price
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