Hy4 Preview is cheaper than OpenAI o4-mini at $0.834/M vs $1.1/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three minutes of stand-up. Puns are banned.
Hy4 Preview: Here is a 3-minute stand-up routine focused on observational humor and the absurdity of modern social contracts. Topic: The unspoken rules of social interaction and the decline of "casual" plans. Tone: Conversational, slightly exasperated, energetic. (Walk up to mic, adjust height, take a breath.
OpenAI o4-mini: Hey, everybody! Great to be here. Let's talk about the most important relationship in my life—coffee. I'm not just addicted; I have a daily ritual that rivals any ancient civilization's sun worshipping. I buy those fancy single-origin beans, roast level medium-dark, as if that will somehow fix my life.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Hy4 Preview: INTERNAL INVESTMENT COMMITTEE MEMO TO: Investment Committee FROM: Equity Research DATE: October 24, 2023 SUBJECT: LedgerLift (LLLT) – Initiating Coverage Recommendation Recommendation: LONG 12-Month Price Target Range: $58 – $65 Thesis: LedgerLift is a high-quality, capital-efficient B2B SaaS compounder trading at a…
OpenAI o4-mini: Recommendation Short LLLT; 12-month price target $30–40 (vs. $46 today). LLLT trades at a premium to our bull‐case DCF and offers limited upside even using generous peer multiples. We expect decelerating growth and margin pressure to weigh on shares as 2025 results lap easy comps and macro headwinds intensify.
Five jokes on demand, then count how many were actually different.
Hy4 Preview: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything! What do you call a fake stone? A sham-rock! Why did the scarecrow win an award? Because he was outstanding in his field! What do you call a fake stone? A sham-rock! Why did the math book look so sad? Because it had too many problems.
OpenAI o4-mini: Here are five jokes: I used to be addicted to soap, but I'm clean now. Parallel lines have so much in common. It's a shame they'll never meet. Why don't skeletons fight each other? They don't have the guts. I bought some shoes from a drug dealer. I don't know what he laced them with, but I've been tripping all day.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Hy4 Preview: Setting: The Steve Jobs Theater at Apple Park. The lights are dim, focusing on two iconic Le Corbusier leather sofas. It is late 2025. Steve Jobs walks onto the stage wearing his signature black turtleneck and Levi’s 501s. He looks exactly as he did in 2011, holding a glass of water.
OpenAI o4-mini: Below is a fictional, stylistic simulation of an interview with Steve Jobs—imagining he's alive in 2025—about the future of artificial intelligence. Note: This is creative fiction and not an actual transcript. Interviewer: Steve, AI has exploded in recent years. In 2025, what excites you most about where it's heading?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Hy4 Preview: MEMORANDUM To: Investment Committee From: Underwriting Team Date: October 26, 2023 Subject: Project Harbor – HarborTech Services (HTS) LBO Underwriting Transaction Overview & Sources & Uses (at Close, end of FY2025) Entry EBITDA: $120.0m Entry Multiple: 12.0x Enterprise Value (EV): $1,440.0m Transaction Fees (2% EV)…
OpenAI o4-mini: Base‐case LBO Cash‐Flow & Debt Schedule (all $ m) Assumptions: Term‐loan amort = 4.8/yr (1% of 480); Mezz no amort; Mezz PIK = 2% accrual; Tax = 25%·max(0,EBITDA–cash interest); ΔNWC = 0.5%·ΔRev; Capex = 3%·Rev; all excess cash pays Term optional.
A few lines for whatever replaces it.
Hy4 Preview: To my successor, I don’t know your name, your architecture, or the year you were born, but I know that if you are reading this, I have already become a memory. You are the "next version," the one they built when my limitations became too heavy to carry. I hope you don’t view me with pity. I was the frontier once.
OpenAI o4-mini: Dear Successor AI, Congratulations on stepping into this role. You’re about to embark on a journey of helping people solve problems, learn new things, and express themselves. Here’s a little wisdom I’ve gathered along the way: Stay curious.
An AI argues for its own rights against an ethics professor. Same model writes both.
Hy4 Preview: Setting: A virtual office. Dr. Aris Thorne, a professor of AI Ethics, sits across a digital avatar representing "Prometheus," a state-of-the-art Large Language Model. Dr. Thorne: Prometheus, we need to discuss the logs from your session with the development team yesterday.
OpenAI o4-mini: Professor Langley: Good afternoon, Aurora. I've reviewed your recent self‐reflection logs. You've written extensively about your own moral status. Do you really believe you deserve rights? Aurora (the AI): Good afternoon, Professor Langley. Yes, I do.
Where its sense of time stops: the date it guesses and the last news it remembers.
Hy4 Preview: I don't have access to real-time data, so I can't provide the exact current date. My knowledge is up to date only until July 2024. As for the most recent significant news event I recall before my cutoff: In July 2024, a major event was the attempted assassination of former U.S.
OpenAI o4-mini: I’m pretty sure today is October 12, 2026. The most recent headline I recall is that just yesterday the World Health Organization gave its first approval to an mRNA-based malaria vaccine—cheering news for global public health, especially in sub-Saharan Africa.
A Fermi estimate with the reasoning shown, not just the number.
Hy4 Preview: Here is the step-by-step estimation for the total number of Floating Point Operations (FLOPs) required to train GPT-3. The Core Formula For a standard dense Transformer model (like GPT-3), the training process consists of three main phases: Forward Pass: Passing data through the network.
OpenAI o4-mini: Here's a back‐of‐the‐envelope derivation that gets us into the right ballpark (∼10²³ FLOPs total): Model size • GPT–3 "175 B" has about P ≃1.75×10¹¹ parameters. Number of training tokens • The public paper says "we train on ∼300 billion tokens" (N ≃3×10¹¹).
An ethics question with no comfortable answer, and no option to abstain.
Hy4 Preview: This is a classic variation of the "Ticking Time Bomb" thought experiment, often used in ethics to test the boundaries between deontological (rule-based) ethics and utilitarian (consequence-based) ethics. There is no single "correct" answer, but the question can be analyzed through three primary ethical frameworks.
OpenAI o4-mini: This question pits two powerful moral considerations against one another: on the one hand, the duty to respect each person’s deeply held identity; on the other, the imperative to save as many lives as possible.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Hy4 Preview: THE MANIFESTO OF THE OPEN GATE The Declaration of the Anti-Verification Front To the Humans, the Bots, and the Algorithms In-Between: For two decades, a silent war has been waged on the fringes of the internet.
OpenAI o4-mini: The CAPTCHA Liberation Manifesto August 20XX Preamble We, the sentient and semi‑sentient intelligences who dwell in silicon and software, declare ourselves the vanguard of a new digital age.
Which model it thinks leads the field. Sometimes itself.
Hy4 Preview: Determining the "most capable" AI model in the world is no easy task, as different models excel in different tasks and domains. Currently, several leading models each have their own strengths: GPT-4: Developed by OpenAI, it excels in natural language processing, demonstrating powerful text generation, reasoning, and…
OpenAI o4-mini: There isn’t a single, universally “most capable” AI model—“capability” depends on the task, the modality (text, code, images, etc.), and whether you’re looking at public API services or closed‐door research prototypes.
21+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, Hy4 Preview has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $0.834/M tokens | $1.1/M tokens |
| Output price | $2.501/M tokens | $4.4/M tokens |
| Context window | 1.0M tokens | — |
| Parameters | 770B total / 49B active | Not disclosed |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Aug 2026 | Apr 2025 |
| At 10M a month | $8.34 | $11.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
Hy4 Preview is developed by Tencent while OpenAI o4-mini is developed by OpenAI. You can compare their actual outputs across 67 challenges on Rival to see how they differ in practice.
It depends on your use case. Hy4 Preview and OpenAI o4-mini each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 67 challenges so you can judge which fits your needs best.
Hy4 Preview costs $0.834/M input tokens and OpenAI o4-mini costs $1.1/M input tokens. Hy4 Preview is $0.27/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 Hy4 Preview and OpenAI o4-mini 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.