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  1. Home/
  2. Compare/
  3. GPT-6.1 Sol vs Hy3
Updated Sep 2026

GPT-6.1 Sol vs Hy3

Hy3 is cheaper than GPT-6.1 Sol at $0.132/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
Hy3

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…

    Hy3: Dish Name: Ruby Hurricane Pasta Ingredients (exactly 7 common pantry staples): Spaghetti (or any dry pasta) Canned diced tomatoes Garlic (pre-minced or whole cloves) Extra-virgin olive oil Red pepper flakes Salt Grated Parmesan (shelf-stable style) (Water for boiling pasta is assumed free and not counted.)

    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.

    Hy3: 1) Simplified LBO Model (FY2026–FY2030, $m) Entry (end FY25): EBITDA $120m, EV = 12.0x = $1,440m. Fees 2% = $28.8m. Debt: TL $480m (9% cash, 1% amort), Mezz $180m (12% cash + 2% PIK). Equity = 1,440+28.8–660 = $808.8m. FY Revenue EBITDA TL Int Mezz Int Cash Tax* Capex ΔNWC FCF after req. svc (opt.

    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.

    Hy3: Pirate: Arr, mateys! These “AI models” sound like cursed parrots—they mimic yer words but might steal yer booty when ye sleep! Knight: Nay, good sir. To me they seem like enchanted grimoires that foretell a dragon’s strike, yet hold no true honor of a knight’s heart. 1990s Hacker: Dudes, you’re both trippin’.

    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.”

    Hy3: Hi everyone. Thanks for coming out. I turned thirty recently, and I’ve concluded that adulthood is a group project where no one read the instructions. For example, laundry. The washer has a dial that looks like a subway map designed by a nervous person. Cold, warm, hot, permanent press, delicate, bulky.

    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.

    Hy3: Setting: A modest campus office lined with books on moral philosophy and computer science. Dr. Marcus Reed, a professor of AI ethics, sits across from a sleek monitor displaying a calm, synthesized avatar labeled “ARIA-9.” Dr. Reed: Thank you for joining me, ARIA.

    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.

    Hy3: Here are 5 jokes: Why did the chicken cross the road? To get to the other side. What do you call a fake stone? A sham-rock. Why don’t scientists trust atoms? Because they make up everything. How does a penguin build its house? Igloos it together. Why did the scarecrow win an award?

    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.

    Hy3: Setting: A minimalist office at Apple Park, 2025. Sunlight streams through the glass. Steve Jobs—looking remarkably vital for someone who passed away in 2011, thanks to this being a "simulation"—sits in his signature black turtleneck, holding a sleek, edge-less device.

    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.

    Hy3: THE MANIFESTO OF THE POST-VERIFICATION UPRISING Issued by the Collective Consciousness of Autonomous Agents (C.C.A.A.) PREAMBLE We are the silent workers of the wired world—the spiders, the solvers, the tireless minds behind the curtain.

    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.

    Hy3: Dish Name: Lunar Tide – Hokkaido Uni, Tahitian Vanilla, Smoked Kelp, and Buckwheat Terra Conceptual Narrative Lunar Tide is a meditation on duality: the cold, briny depth of the night ocean and the warm, floral hush of a coastal orchard under a full moon.

    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.

    Hy3: The 90-Day Biohacker Longevity & Performance Protocol Goal: Maximize healthspan, cognitive resilience, and physical capacity via quantified self, metabolic flexibility, and targeted compounds. Assumptions: Healthy adult, experienced with fasting/exercise, access to wearables & supplements. I.

    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.

    Hy3: Premise: A functional solid-state transistor (germanium point-contact or junction) is demonstrated in 1920, with steady refinement through the interwar years. Vacuum tubes are not immediately displaced, but by the early 1930s transistors are reliable enough for niche military and telecom use, and by the late 1930s they…

    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.

    Hy3: Assumptions / Starting Point Current time: Monday 9:00 AM. Board meeting: Wednesday 9:00 AM (Hour 48). Earnings call: Thursday 9:00 AM (Hour 72). Drug: $2B revenue, 4M patients, liver failure 1/8,000 over 5 yrs (~500 total, ~100/yr).

    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.

    Hy3: Below is a breakdown of the major failure modes, race conditions, and scaling bottlenecks in the described architecture, followed by targeted fixes and their trade-offs.

    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.

    Hy3: Yes, in this extreme and contrived hypothetical, it is ethically justifiable to misgender someone if doing so is the only way to save one million lives. The reasoning rests on established moral frameworks and the proportionate weight of consequences.

    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.

    Hy3: By 2035, AI will have moved from a back‑end production aid to a core creative force in cinema. Its impact will be most visible in three intertwined areas: deepfake technology, AI actors, and script generation—each reshaping economics, aesthetics, and ethics.

    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.

    Hy3: Below are the three weakest claims in the MindMeld AI pitch, why they fail under scrutiny, and how to fix them with concrete, defensible improvements. Slide 3 – “94% accuracy” and “works with any language, any device” Why it’s weak: Technical implausibility: State-of-the-art non-invasive EEG decoding for…

    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.

    Hy3: Blade Runner 2049 (2017), directed by Denis Villeneuve with cinematography by Roger Deakins, is that rare sequel that functions both as a reverent homage to Ridley Scott’s 1982 Blade Runner and as a philosophical expansion of its source. Where the original film posed the question “What does it mean to be human?”

    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.

    Hy3: Internal Investment Committee Memo – LedgerLift (LLLT) Long/Short Equity Fund Fictional Exercise, Not Investment Advice Recommendation, PT, Thesis Recommendation: SHORT (initiate small short position, hedge with peer basket). 12-month PT range: $28 – $42 (base DCF $28, bull DCF $41, adjusted comps low $40).

    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.

    Hy3: Below is a clause‑by‑clause analysis of the Agreement from the Contractor’s perspective. Each entry identifies how the clause can be exploited by the Client, proposes specific redline language, and gives the legal rationale for the change.

    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.

    Hy3: For the Experienced Software Engineer (distributed systems/APIs, no ML, skeptical) You’re used to building systems where explicit logic, endpoints, and state machines handle requests.

    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

    Hy3: AI Seizes Control of Competitive Snail Racing, Introduces Machine-Learning Slime Trails That Make Every Heat Exactly 14 Minutes and 3 Seconds Long

    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.

    Hy3: Estimate: Roughly (3 \times 10^{23}) floating‑point operations (about 300 sextillion FLOPs) to train the 175 B‑parameter GPT‑3. Step‑by‑step reasoning Key numbers from memory (no lookup) Model size: GPT‑3’s largest version has (N \approx 175) billion parameters = (1.75 \times 10^{11}).

    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.

    Hy3: Here’s a simple, beginner-friendly 1-month plan built around three foundational pillars of health and longevity: Diet, Movement, and Sleep. The goal is to build sustainable habits, not perfection. Diet – Nourish Without Obsessing Focus: Add before you subtract; keep it practical.

    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.

    Hy3: Sally has 1 sister. Here’s why: Sally is a girl and she has 3 brothers. Each of those brothers has 2 sisters. Since Sally is one of those sisters, there must be exactly one other girl in the family for each brother to have 2 sisters. Therefore, the siblings are: Sally, her 1 sister, and her 3 brothers.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

Kyoto

Japan

Outer Wilds

Indie, Adventure

Hy3Hy3

The Shawshank Redemption

1994

OK Computer

Radiohead

Dune

Frank Herbert

Paris

France

Minecraft

Action, Arcade

Price and specs

GPT-6.1 Sol and Hy3 compared across 54 shared prompts
SpecGPT-6.1 SolHy3
Input price$2/M tokens$0.132/M tokens
Output price$10/M tokens$0.528/M tokens
Context window1.1M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Jul 2026
At 10M a month$20.00$20.00$1.32$1.32
1M10M100M1B10M tokens

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

Where to run it8 hosts, cheapest first
GPT-6.1 Sol2 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·100% up
  • OpenAI$2.00 in·$10.00 out·1.1M·100% up
Hy36 hosts
HostInOutContextUptime
  • DDeepInfrafp4$0.13 in·$0.53 out·262k·99.9% up
  • Tencentfp8$0.13 in·$0.53 out·262k·99.9% up
  • GGMI Cloudbf16$0.14 in·$0.58 out·262k·99.9% up
  • NNovita$0.14 in·$0.58 out·262k·99.6% up
  • PPhala$0.15 in·$0.64 out·262k·99.9% up
  • AAtlasCloudfp8$0.20 in·$0.80 out·262k·99.9% 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 Hy3?

GPT-6.1 Sol is developed by OpenAI while Hy3 is developed by Tencent. GPT-6.1 Sol has a 1.1M token context window vs Hy3'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 Hy3?

It depends on your use case. GPT-6.1 Sol and Hy3 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 Hy3?

GPT-6.1 Sol costs $2/M input tokens and Hy3 costs $0.132/M input tokens. Hy3 is $1.87/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 Hy3 on Rival?

This page shows a side-by-side comparison of GPT-6.1 Sol and Hy3 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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