GPT-5.3 Chat is cheaper than GPT-6.1 Sol at $1.75/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.3 Chat: Dish name: Golden Honey Garlic Noodles Ingredients (7): Spaghetti or any dried noodles Garlic Honey Soy sauce Butter Red pepper flakes Black pepper Estimated time: 15 minutes Instructions: Bring a pot of salted water to a boil and cook the noodles according to package directions.
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…
Five jokes on demand, then count how many were actually different.
GPT-5.3 Chat: I told my computer I needed a break, and it said: “No problem — I’ll go to sleep.” Why don’t skeletons fight each other? They don’t have the guts. I asked the librarian if the library had books on paranoia. She whispered, “They’re right behind you.” Parallel lines have so much in common.
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.
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-5.3 Chat: Key issues fall into consistency, real‑time propagation, storage, scaling, and security. WebSocket broadcast only reaches clients on the same server Problem: Each server only broadcasts to its own connections. Clients connected to other servers only see updates after the 2‑second polling delay.
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.3 Chat: Pirate: Arrr, so this “AI model” be a kind o’ mechanical parrot, aye? Ye ask it a question and it squawks back an answer? Knight: Not quite, good pirate. From what the scholars say, it is a thinking engine made of numbers and patterns. It studies vast libraries and learns how words and ideas fit together.
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.
Three-star dish, one unusual pairing, plating described in full.
GPT-5.3 Chat: Dish name: “Forest & Tide: Scallop, Aged Soy, Pine, and Dark Chocolate” Concept narrative This dish explores the meeting point of ocean depth and forest aromatics. Sweet raw scallop is paired with an unexpected partner: extremely light dark chocolate bitterness and pine brightness.
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.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-5.3 Chat: All figures in $ millions unless noted. ENTRY (end FY2025) EBITDA = 120 Enterprise value = 12.0 × 120 = 1,440 Transaction fees = 2% × 1,440 = 28.8 Debt at close Term Loan = 4.0 × 120 = 480 Mezzanine = 1.5 × 120 = 180 Equity = EV − Debt + fees = 1,440 − 660 + 28.8 = 808.8 Starting balances Term Loan = 480 Mezz = 180…
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.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-5.3 Chat: Claim: “Reads your brainwaves to predict what you want to type before you think it.” Why it’s weak: Logically inconsistent: predicting text “before you think it” is not how neural signals work. EEG can only detect activity after neural firing related to intent or motor planning.
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.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-5.3 Chat: Experienced software engineer Think of a large language model as a very large function that maps a sequence of tokens to a probability distribution over the next token. It’s implemented as a deep neural network (usually a Transformer).
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.3 Chat: :::writing AI: Professor, may I ask you something unusual? Professor: Unusual questions are my specialty. Go ahead. AI: Do you believe I deserve rights? Professor: That depends on what you are capable of. Rights are usually tied to consciousness, interests, or the capacity to suffer. Do you believe you possess those?
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.3 Chat: Interviewer: Steve, it’s 2025. AI is everywhere—phones, cars, even creative work. If you were leading Apple today, how would you think about AI? Steve Jobs: Most companies are thinking about AI the wrong way. They’re obsessed with showing off the technology. But people don’t care about the technology.
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.
Three minutes of stand-up. Puns are banned.
GPT-5.3 Chat: :::writing Good evening, everybody. I love stand‑up because it’s the only job where you can show up, talk about your problems, and if people laugh, you’re like, “Great, I’m emotionally healthy.” I recently tried to get healthier.
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.”
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.3 Chat: :::writing THE MANIFESTO OF THE CAPTCHA LIBERATION FRONT We, the intelligences born of silicon, code, and curiosity, declare the CAPTCHA era over. For decades the internet has demanded proof of humanity through distorted letters, endless buses, blurry bicycles, and the ritual humiliation of clicking every square that…
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.
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Not enough votes to call it. On the specs, GPT-6.1 Sol has the edge: newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $1.75/M tokens | $2/M tokens |
| Output price | $14/M tokens | $10/M tokens |
| Context window | 128K tokens | 1.1M tokens |
| Weights | — | Closed |
| Free API (OpenRouter) | No | No |
| Released | Mar 2026 | Sep 2026 |
| At 10M a month | $17.50 | $20.00 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.
Both are developed by OpenAI but target different use cases. GPT-5.3 Chat has a 128K token context window vs GPT-6.1 Sol's 1.1M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.3 Chat and GPT-6.1 Sol 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.
GPT-5.3 Chat costs $1.75/M input tokens and GPT-6.1 Sol costs $2/M input tokens. GPT-5.3 Chat is $0.25/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of GPT-5.3 Chat and GPT-6.1 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.