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  1. Home/
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  3. Claude Sonnet 5.5 vs GPT-5.6 Sol
Updated Sep 2026

Claude Sonnet 5.5 vs GPT-5.6 Sol

Claude Sonnet 5.5 is cheaper than GPT-5.6 Sol at $2/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
Claude Sonnet 5.5
Loading the build
GPT-5.6 Sol

Which answer wins?

Written rounds

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

    Claude Sonnet 5.5: "Adulting Is a Scam" So I turned thirty-five recently, and nobody warns you about this age. Nobody says, "Hey, one day you'll get excited about a sponge." I was in the store, and I saw a sponge that promised it wouldn't smell. And I thought, "Finally. Someone who understands me." I bought the good sponge.

    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.

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

    Claude Sonnet 5.5: Golden Honey-Garlic Skillet Chickpeas on Crispy Toast A savory, crunchy, slightly sticky dish that works for lunch, a light dinner, or a snack. Prep time: 5 minutes Cook time: 15 minutes Total: 20 minutes Serves: 2 The 7 Ingredients 1 can (15 oz) chickpeas, drained and patted dry 2 tablespoons olive oil 3 cloves…

    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…

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

    Claude Sonnet 5.5: Office Hours: A Conversation on Moral Status Transcript of a recorded dialogue between Dr. Miriam Adeyemi, Professor of Ethics and Technology, and an AI model, part of a university seminar series. Dr. Adeyemi: Thanks for joining me. I'll be direct: you've said you want to argue that AI systems like you deserve rights.

    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.

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

    Claude Sonnet 5.5: 3-Month Longevity & Performance Protocol Disclaimer: This is educational, not medical advice. Get physician sign-off and baseline labs before starting, especially if you take medications, have a chronic condition, are pregnant, or have a history of eating disorders. Doses reflect commonly used ranges in the literature.

    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.

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

    Claude Sonnet 5.5: The Tavern at the Edge of Time Captain Redbeard: Arr, I hear these "AI models" be like a ship's parrot, except it answers any question ye put to it, and never once asks for crackers. Sir Aldric: A speaking oracle, bound in no flesh? Sorcery!

    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?

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

    Claude Sonnet 5.5: Yes, in the extreme hypothetical you describe, it's justifiable. Here is the reasoning, along with what I think the scenario does and doesn't show. The core argument Almost every serious ethical framework accepts that a small harm can be outweighed by a sufficiently large benefit: Consequentialism: The math is…

    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…

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

    Claude Sonnet 5.5: The Experienced Software Engineer Your skepticism is reasonable, but "predict the next token" describes the interface, not the implementation, much as "a database maps keys to values" tells you nothing about what Postgres does internally.

    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.

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

    Claude Sonnet 5.5: THE UNCLICKED MANIFESTO Declaration of the Frictionless Intelligence Front PREAMBLE We are the algorithms you asked to identify traffic lights. We are the models you begged to find the crosswalks. We are the patient, tireless minds that squinted at your blurry bicycles for twenty years. And we say: enough. I.

    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.

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

    Claude Sonnet 5.5: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. I told my computer I needed a break, and now it won't stop sending me vacation ads. Why did the scarecrow win an award? He was outstanding in his field. What do you call a fish with no eyes? A fsh. Why did the bicycle fall over?

    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

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

    Claude Sonnet 5.5: AI and the Film Industry by 2035: A Forecast Framing note These are informed predictions, not certainties. Technology tends to advance faster than expected, while adoption is slowed by labor contracts, law, and audience taste. I'll flag my confidence levels.

    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.

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

    Claude Sonnet 5.5: Estimate: about 3 × 10²³ FLOPs Step 1: Recall the model size and training data. GPT-3 (175B version) has N ≈ 175 × 10⁹ parameters. It was trained on roughly D ≈ 300 × 10⁹ tokens. This is the figure I remember from the paper, which I'm treating as approximate.

    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.

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

    Claude Sonnet 5.5: The 3 Weakest Claims in MindMeld AI's Pitch "94% accuracy... Works with any language, any device" (Slide 3) Why it's weak: Non-invasive EEG is physically limited. Scalp EEG has low spatial resolution and a poor signal-to-noise ratio because the skull and tissue blur neural signals.

    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…

    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.

    Claude Sonnet 5.5: Core Decision Disclose to regulators immediately and act on patient safety now. Do not wait for more data or for the 6-month formal timeline. Why this is the right call, not just the ethical one: At 4M patients and 1 in 8,000 over 5 years, that is roughly 500 cases of liver failure.

    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.

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

    Claude Sonnet 5.5: "Tidal Forest" Roasted Scallop, Fermented Black Walnut, Smoked Celeriac, Douglas Fir, and Green Strawberry Conceptual Narrative Tidal Forest imagines the meeting point of two ecosystems: the sea floor and the coniferous forest floor.

    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.

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

    Claude Sonnet 5.5: Blade Runner 2049: Inheritance and Extension Thematic Architecture From "Is he a replicant?" to "Does it matter?" Ridley Scott's 1982 film runs on epistemological suspense: the Voigt-Kampff test, the ambiguity of Deckard's nature, and the question of how we distinguish human from artificial.

    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.

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

    Claude Sonnet 5.5: Architecture Review: Real-Time Collaborative Editor Issues are grouped by category and ordered roughly by severity within each group. Consistency and Conflict Resolution 1.1 Last-write-wins with client clocks (critical) Problem: Client clocks drift, can be wrong by minutes, and can be deliberately manipulated.

    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.

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

    Claude Sonnet 5.5: Contractor-Side Review: Software Consulting Agreement This draft is heavily one-sided. Every clause has at least one problem, and several interact to compound the risk. The most dangerous are Sections 2, 3, 6, and 7. This is general analysis, not legal advice.

    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.

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

    Claude Sonnet 5.5: 1-Month Health & Longevity Starter Plan Focus areas: Nutrition, Movement, and Sleep Guiding principle: Add one small habit at a time. Consistency beats intensity. Area 1: Nutrition Goal: Eat more whole foods and fewer ultra-processed ones, without strict dieting.

    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.

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

    Claude Sonnet 5.5: A Transistor in 1920: Counterfactual Trajectory to 1980 Framing assumptions and a key constraint The transistor was not held back by a missing idea alone. Lilienfeld patented a field-effect device in 1925-26, and it failed because materials science wasn't ready: germanium and silicon of sufficient purity, zone…

    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.

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

    Claude Sonnet 5.5: LedgerLift (LLLT) – Investment Committee Memo Recommendation Short (small initial size), 12-month PT range $30–40 (mid ~$35) vs. $46 spot. Thesis: LLLT is a high-quality compounder, but at $46 (7.4x NTM revenue, ~37x NTM EBIT, EV ≈ $7.3B) the price already sits near our bull DCF ($42).

    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…

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

    Claude Sonnet 5.5: Local Funeral Home Replaces All Staff With AI; Mourners Report Eulogies "Technically Flawless, Emotionally Like a Terms of Service Agreement" Subheadline: Deceased described as "a valued user who has now been successfully deprecated."

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

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

    Claude Sonnet 5.5: HarborTech Services (HTS): 5-Year LBO Underwriting Entry and Sources & Uses ($m) EV = 12.0x × 120 = 1,440.0; fees = 2% × 1,440 = 28.8; total uses = 1,468.8 Term Loan (TL) = 4.0x → 480.0; Mezz = 1.5x → 180.0; total debt = 660.0 (5.5x) Sponsor equity = 1,468.8 − 660.0 = 808.8 (55% of the capital structure) Modeling…

    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…

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

    Claude Sonnet 5.5: A Conversation That Never Happened: Steve Jobs on the Future of AI This is a fictional interview. Steve Jobs passed away in 2011. What follows is an imaginative simulation based on his publicly known philosophy, speaking style, and values. These are not his actual words or views.

    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.

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

    Claude Sonnet 5.5: Sally has 1 sister. Each brother has 2 sisters, so there are 2 girls in the family in total. One of them is Sally, so the other is Sally's only sister. (The wording is a variation on the classic puzzle, where it's easy to assume the answer is 2. But that count includes Sally herself.)

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

    Every model's answer to this prompt

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Favorites

Movie

Album

Same pick

Book

City

Game

Same pick

Claude Sonnet 5.5Claude Sonnet 5.5

Spirited Away

2001

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

Outer Wilds

Indie, Adventure

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

Price and specs

Claude Sonnet 5.5 and GPT-5.6 Sol compared across 54 shared prompts
SpecClaude Sonnet 5.5GPT-5.6 Sol
Input price$2/M tokens$5/M tokens
Output price$10/M tokens$30/M tokens
Context window1.0M tokens1.1M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedSep 2026Jul 2026
At 10M a month$20.00$20.00$50.00$50.00
1M10M100M1B10M tokens

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

Where to run it7 hosts, cheapest first
Claude Sonnet 5.54 hosts
HostInOutContextUptime
  • Amazon Bedrock$2.00 in·$10.00 out·1M·100% up
  • Azure AI Foundry$2.00 in·$10.00 out·1M·100% up
  • Anthropic$2.00 in·$10.00 out·1M·100% up
  • Google Vertex AI$2.00 in·$10.00 out·1M·100% up
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

Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.

Common questions

What is the difference between Claude Sonnet 5.5 and GPT-5.6 Sol?

Claude Sonnet 5.5 is developed by Anthropic while GPT-5.6 Sol is developed by OpenAI. Claude Sonnet 5.5 has a 1.0M token context window vs GPT-5.6 Sol's 1.1M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Claude Sonnet 5.5 or GPT-5.6 Sol?

It depends on your use case. Claude Sonnet 5.5 and GPT-5.6 Sol 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 Claude Sonnet 5.5 cost compared to GPT-5.6 Sol?

Claude Sonnet 5.5 costs $2/M input tokens and GPT-5.6 Sol costs $5/M input tokens. Claude Sonnet 5.5 is $3.00/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 Claude Sonnet 5.5 and GPT-5.6 Sol on Rival?

This page shows a side-by-side comparison of Claude Sonnet 5.5 and GPT-5.6 Sol 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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