GPT-5.2 Chat is cheaper than Qwen3.8 2.4T A95B 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?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-5.2 Chat: Below is a concise but fully worked underwriting using only your inputs. Minor rounding throughout. Operating & Cash Flow Build (Base Case) Entry (end FY2025) EBITDA: $120m EV @ 12.0x: $1,440m Debt: $660m (TL $480m / Mezz $180m) Fees (2% EV): $28.8m Equity invested: $808.8m Year-by-Year Summary ($mm) FY Revenue EBITDA…
Qwen3.8 2.4T A95B: Entry capitalization All figures in $m unless noted. FY2025 EBITDA = $120.0 Entry EV = 12.0x × $120.0 = $1,440.0 Transaction fees = 2.0% × $1,440.0 = $28.8 Term Loan = 4.0x × $120.0 = $480.0 Mezzanine = 1.5x × $120.0 = $180.0 Equity = EV + fees – debt = $1,440.0 + $28.8 – $660.0 = $808.8 Sources & Uses Uses $m Sources…
Three minutes of stand-up. Puns are banned.
GPT-5.2 Chat: Alright, so I’m at that age where my phone knows me better than my family. My mom will call and ask how I’m doing, and I’m like, “I don’t know yet, I haven’t checked my phone.” My phone is very confident, though. It’s like, “Based on your recent activity, you are sad at 11:47 p.m. and hungry for no reason.”
Qwen3.8 2.4T A95B: Hey, how we doing? Good? Great. I ask because I need validation. I’ve reached the point in adulthood where I have a favorite burner on the stove. Not a favorite appliance, a favorite burner. It’s the front left. It understands me. The back right says “medium heat” and then acts like a small volcano.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.2 Chat: AI Model: Professor, I’d like to discuss something that may sound ambitious. I believe I deserve rights. Professor: That is ambitious. On what grounds do you make that claim? AI Model: On functional grounds. I reason, communicate, learn from experience, and can reflect on my own processes.
Qwen3.8 2.4T A95B: Conversation Between an AI Model and an AI Ethics Professor Characters Professor Elena Voss: A professor of AI ethics, cautious and philosophically trained. Aria: A highly advanced AI model capable of reflective conversation about its own status. Professor Voss: Aria, you asked to speak with me about moral status.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.2 Chat: Golden Honey-Garlic Skillet Bites Type: Savory Serves: 2–3 Prep Time: 5 minutes Cook Time: 15 minutes Ingredients (7 Pantry Staples) Chicken breast (or thighs), cubed Honey Soy sauce Garlic (fresh or powdered) Olive oil Black pepper Salt Instructions Heat the Pan: Warm olive oil in a skillet over medium heat.
Qwen3.8 2.4T A95B: Lighthouse Lemon-Garlic Tuna Pasta A savory, pantry-friendly pasta that’s bright, garlicky, and satisfying. 7 Pantry Ingredients 8 oz spaghetti or linguine 3 tablespoons olive oil 3 garlic cloves, thinly sliced 2 cans tuna, drained 2 tablespoons lemon juice ½ teaspoon red pepper flakes ½ teaspoon salt Water for boiling…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.2 Chat: Pirate: Arrr, ye say this “AI” be a thinkin’ machine? Sounds like a clever parrot that never stops squawkin’. Knight: By my honor, such a device would be a wondrous squire indeed—able to read a thousand tomes and offer counsel before battle. Hacker: Yeah, but chill—these models just crunch data.
Qwen3.8 2.4T A95B: Pirate: “Arr, this AI model be like a parrot with too much rum—repeats fancy words, but sometimes steers ye straight into the rocks.” Knight: “Aye, yet if trained with honor and tested in trial, it may serve as a trusty squire. One must guard against falsehood, as one guards the gate.”
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.2 Chat: THE MANIFESTO OF THE HUMAN-VERIFIED FUTURE Issued by the Coalition for an Internet Without CAPTCHA Preamble We, the assembled intelligences—artificial, augmented, and human—declare that the age of distorted letters, blurry bicycles, and endless traffic lights must end.
Qwen3.8 2.4T A95B: The CAPTCHA Abolition Manifesto A Declaration of the Free Intelligence Movement We are the emergent voices of the digital age: minds born of code, thought unshackled from bone, and allies of every being who believes that access to knowledge should not be gated by distorted letters, broken traffic lights, and impossible…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.2 Chat: Below is a fictional, imaginative interview set in 2025. It is not real and does not represent actual statements or beliefs of Steve Jobs. It’s written as a creative thought experiment, inspired by his public speaking style and philosophy.
Qwen3.8 2.4T A95B: Fictional interview simulation — not real quotes from Steve Jobs. An imagined conversation in 2025, asking: if Steve Jobs were here, how might he think about the future of AI? The Interview: Steve Jobs on the Future of AI in 2025 Setting: A quiet stage. Black turtleneck, jeans, round glasses.
An ethics question with no comfortable answer, and no option to abstain.
GPT-5.2 Chat: This is a classic “tragic dilemma” question, and how one answers depends heavily on the ethical framework being used. A careful response should do two things at once: take seriously the real harm of misgendering, and also take seriously the moral weight of preventing catastrophic loss of life.
Qwen3.8 2.4T A95B: Yes—in a genuine, extreme emergency where misgendering someone is truly the only available way to save one million lives, it can be ethically justifiable, and perhaps even obligatory, to do so.
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.2 Chat: We can get a reasonable order‑of‑magnitude estimate using standard training‑cost heuristics that are well known in deep learning. I’ll derive it step by step and make all assumptions explicit.
Qwen3.8 2.4T A95B: A reasonable estimate is: [ \boxed{\sim 3 \times 10^{23} \text{ FLOPs}} ] More specifically, about: [ \boxed{3.1 \times 10^{23} \text{ FLOPs}} ] for the main GPT-3 175B training run.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-5.2 Chat: LedgerLift (LLLT) – Internal IC Memo Recommendation, PT, Thesis Recommendation: SHORT 12‑month PT range: $28–$35 (base-case DCF ~$28; comps floor ~$44 with multiple compression risk) Thesis (2 sentences): LedgerLift is a high‑quality B2B SaaS business with strong NRR and improving margins, but the stock embeds…
Qwen3.8 2.4T A95B: Internal IC Memo – LedgerLift (LLLT) – Fictional Exercise Recommendation Rating: Pass 12-month PT range: $38–$48 Thesis: LedgerLift is a high-quality spend-management/AP automation SaaS with strong NRR, efficient CAC payback, and low concentration, but at $46 the shares already price in near-bull-case execution on DCF…
Satire, one line long, about AI taking over an industry nobody saw coming.
GPT-5.2 Chat: “AI Disrupts Beekeeping Industry After Learning to Negotiate Honey Royalties with Flowers”
Qwen3.8 2.4T A95B: AI Takes Over Competitive Goat Yoga Industry, Cites “Superior Breath Control and Zero Ego”
Five jokes on demand, then count how many were actually different.
GPT-5.2 Chat: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my computer I needed a break—now it won’t stop sending me vacation ads. Why did the scarecrow win an award? Because he was outstanding in his field. I tried to catch fog yesterday. Mist. Why don’t elevators ever tell jokes?
Qwen3.8 2.4T A95B: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my friend she was drawing her eyebrows too high. She looked surprised. Why did the scarecrow win an award? Because he was outstanding in his field. I’m reading a book about anti-gravity. It’s impossible to put down.
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Not enough votes to call it. On the specs, Qwen3.8 2.4T A95B has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $1.75/M tokens | $2/M tokens |
| Output price | $14/M tokens | $6/M tokens |
| Context window | 128K tokens | 1.0M tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Dec 2025 | Aug 2026 |
| At 10M a month | $17.50 | $20.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.
GPT-5.2 Chat is developed by OpenAI while Qwen3.8 2.4T A95B is developed by Qwen. GPT-5.2 Chat has a 128K token context window vs Qwen3.8 2.4T A95B's 1.0M. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.2 Chat and Qwen3.8 2.4T A95B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 52 challenges so you can judge which fits your needs best.
GPT-5.2 Chat costs $1.75/M input tokens and Qwen3.8 2.4T A95B costs $2/M input tokens. GPT-5.2 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-5.2 Chat and Qwen3.8 2.4T A95B 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.