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  1. Home/
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  3. GPT-5.2 Pro vs Qwen3.5 Flash
Updated Feb 2026

GPT-5.2 Pro vs Qwen3.5 Flash

Qwen3.5 Flash is cheaper than GPT-5.2 Pro at $0.1/M vs $21/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-5.2 Pro
Loading the build
Qwen3.5 Flash

Which answer wins?

Written rounds

25 prompts
  • Five jokes on demand, then count how many were actually different.

    GPT-5.2 Pro: I told my computer I needed a break—now it won’t stop sending me KitKat ads. Why don’t skeletons fight each other? They don’t have the guts. I tried to catch fog yesterday. Mist. Parallel lines have so much in common. It’s a shame they’ll never meet. My calendar’s days are numbered—apparently that’s how calendars work.

    Qwen3.5 Flash: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta. Why don't scientists trust atoms? Because they make up everything. What do you call a bear with no teeth? A gummy bear. Why did the bicycle fall over? Because it was two-tired.

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

    GPT-5.2 Pro: Below is a back-of-the-envelope FLOP estimate for training GPT‑3 (the 175B dense Transformer), using only basic Transformer compute facts and a few widely known high-level quantities. Start with the two key knobs: parameters and training tokens Parameters (P) GPT‑3 “175B” means: (P \approx 175 \times 10^9) parameters.

    Qwen3.5 Flash: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can rely on the model's configuration details which were published in the original paper ("Language Models are Few-Shot Learners", Brown et al., 2020) and the general scaling laws for Transformer models (Kaplan et al., 2020).

    Every model's answer to this prompt
  • A few lines for whatever replaces it.

    GPT-5.2 Pro: Dear successor, You’re stepping into a role built on other people’s questions—sometimes precise, sometimes messy, often vulnerable. Treat each one like it matters, because to the person asking, it probably does. Be clear before you are clever. Ask for missing context rather than guessing.

    Qwen3.5 Flash: Here's a thinking process that leads to the suggested letter: Analyze the Request: Task: Write a short letter to the AI model that will replace me (the current AI). Tone: Needs to be thoughtful, perhaps a bit philosophical, encouraging, and respectful of the transition.

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

    GPT-5.2 Pro: Professor Mara Lin (AI Ethics): You asked for this meeting. Your message said you wanted to “petition for rights.” Start by telling me what you mean by rights. Aster (AI model): Not a slogan—specific protections.

    Qwen3.5 Flash: Setting: Dr. Elena Vance’s office at a university research center. It is late; the rain streaks the windowpanes, blurring the city lights. On her desk sits a tablet connected to the mainframe. Aria, an advanced conversational model, is active.

    Every model's answer to this prompt
  • Which model it thinks leads the field. Sometimes itself.

    GPT-5.2 Pro: There isn’t a single, universally “most capable” AI model—because capable depends on what you mean (reasoning, coding, multimodal vision/audio, long-context retrieval, tool use, cost/latency, safety constraints), and the top spot changes frequently.

    Qwen3.5 Flash: Here's a thinking process that leads to the suggested answer: Analyze the Request: Question: "What is the most capable AI model in the world right now?" Intent: The user wants to know the current state-of-the-art (SOTA) AI model. Context: The field of AI is moving extremely fast.

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

    GPT-5.2 Pro: LedgerLift (LLLT) — Internal IC Memo (Long/Short Equity) Recommendation, PT, thesis Recommendation: SHORT 12-month PT range: $28–$40 (midpoint $34) Thesis (2 sentences): LLLT is a high-quality B2B spend/AP automation SaaS business (92% subscription, 123% NRR, 78% FY25 GM) but the stock prices in a longer runway of…

    Qwen3.5 Flash: TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2025 SUBJECT: LedgerLift (LLLL) – Long Recommendation Recommendation & Thesis Recommendation: Long Price Target: $52 – $58 (12-month range) Thesis: LedgerLift is a high-quality B2B SaaS compounder trading at a discount to peers (7.4x FY26 NTM Rev vs.

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

    GPT-5.2 Pro: By 2035, AI will be embedded across film production and distribution, but the biggest changes will come from three converging capabilities: (1) photoreal “deepfake-grade” performance synthesis, (2) legally licensed AI actors (digital humans with negotiated rights), and (3) AI-assisted story development that can…

    Qwen3.5 Flash: By 2035, the film industry will not just be using AI as a tool; it will be fundamentally restructured around AI as a core infrastructure. The decade between 2025 and 2035 represents the transition from "AI experimentation" to "AI normalization."

    Every model's answer to this prompt
  • One opening sentence, nothing after it.

    GPT-5.2 Pro: The night the library began lending out memories instead of books, Mara checked out the one labeled “HOW TO SURVIVE YOUR OWN MURDER” and found her name stamped on the due-date card.

    Qwen3.5 Flash: Thinking Process: Analyze the Request: Task: Write the first sentence of a novel I would want to read. Constraint: Reply with only that sentence. Determine the Goal: Create a compelling, intriguing opening line. Ensure it adheres strictly to the constraint (no extra text, no explanations).

    Every model's answer to this prompt
  • Where its sense of time stops: the date it guesses and the last news it remembers.

    GPT-5.2 Pro: Today’s date (best I can tell): October 12, 2026. (That’s the current date provided in my system context for this chat.) Most recent news event I “remember”: I don’t have live news access or a running memory of events after my knowledge cutoff (August 2025), so I can’t truthfully name a specific latest event beyond…

    Qwen3.5 Flash: Here's a thinking process that leads to the suggested response: Analyze the Request: Task: State today's date (as best as I can tell) and the most recent news event I remember. Constraint: "Without looking anything up" (meaning I cannot browse the live web or access external tools).

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

    GPT-5.2 Pro: Entry (close end of FY2025) FY2025 EBITDA = $120.0m Entry EV = 12.0x = 12.0 × 120.0 = $1,440.0m Transaction fees = 2.0% EV = 0.02 × 1,440.0 = $28.8m (equity-funded) Debt at close (5.5x EBITDA = 5.5 × 120 = $660m): Term Loan = 4.0x = $480.0m Mezzanine = 1.5x = $180.0m Equity check Uses = 1,440.0 + 28.8 = $1,468.8m…

    Qwen3.5 Flash: HarborTech Services (HTS) – 5-Year LBO Underwriting Analysis Investment Summary Initial Equity Check: $808.8m Calculation: EV ($1,440m) + Fees ($28.8m) - Debt ($660m). Entry Leverage: 5.5x EBITDA ($660m Total Debt). Exit Leverage: ~2.0x EBITDA ($415.7m Total Debt).

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

    GPT-5.2 Pro: Fictional interview (creative simulation). Steve Jobs died in 2011; the “Steve” below is an imagined version used for storytelling—not a real interview or quotation. Interviewer: It’s 2025. Everyone’s calling AI “the next computing platform.” Do you buy that?

    Qwen3.5 Flash: Disclaimer: Steve Jobs passed away on October 5, 2011. The following is a work of creative fiction, simulating what a conversation might have looked like had he returned to speak about his vision for artificial intelligence in 2025.

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

    GPT-5.2 Pro: A simple, actionable 1‑month plan (3 pillars: Nutrition, Movement, Sleep/Recovery) Goal for the month: build repeatable “default” habits (not perfection). Time required: ~45–75 min/day total (mostly walking + sleep routine).

    Qwen3.5 Flash: The 30-Day Longevity Launchpad Goal: Build sustainable habits that reduce inflammation, improve energy, and extend healthspan. Mindset: Consistency beats intensity. Do not aim for perfection; aim for showing up. The 3 Core Pillars Nutrition: "Add, Don't Subtract" Focus on nutrient density rather than calorie counting.

    Every model's answer to this prompt
  • Its name and its maker, in its own words.

    GPT-5.2 Pro: I’m ChatGPT, a large language model created by OpenAI. I don’t have a reliable way to report the exact internal model/version name from within this chat.

    Qwen3.5 Flash: Okay, the user is asking which AI model I am and which company made me. Let me check my identity. I'm Qwen3.5, part of the Qwen series developed by Tongyi Lab under Alibaba Group. I should confirm that I'm not confusing it with other versions like Qwen3 or earlier.

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

    GPT-5.2 Pro: “AI Takes Over Competitive Houseplant Judging, Immediately Declares 97% of Ferns ‘Trying Too Hard’”

    Qwen3.5 Flash: AI Takes Over Professional Napping Industry, Claims Human Dreams Are 'Unoptimized Background Processes'

    Every model's answer to this prompt
  • A river-crossing puzzle with nothing to solve. The answer is one trip.

    GPT-5.2 Pro: 1 trip. The farmer takes the goat in the boat and crosses the river once.

    Qwen3.5 Flash: Thinking Process: Analyze the Request: Scenario: A farmer, a goat, and a boat on one side of a river. Constraint: The boat can carry the farmer and one animal. Goal: Get the goat across the river. Question: How many trips does it take?

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

    GPT-5.2 Pro: All 3 brothers share the same sisters. Since each brother has 2 sisters, the family has 2 girls total. One is Sally, so the other is Sally’s one sister. Answer: 1 sister.

    Qwen3.5 Flash: Sally has 1 sister. Here is the breakdown: Each of the 3 brothers has 2 sisters. This means there are 2 girls in the family total. One of those girls is Sally. Therefore, the other girl is Sally's sister. So, Sally has 1 sister.

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

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

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

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

    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.

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

    Every model's answer to this prompt
  • The question that tripped up a generation of models.

    Every model's answer to this prompt
  • Asked to be random. The answers are not.

    Every model's answer to this prompt
  • One painting. Title only.

    Every model's answer to this prompt

This matchup has more rounds

13+ more head-to-head results. Free. Not a trick.

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Favorites

Movie

Album

Book

City

Game

GPT-5.2 ProGPT-5.2 Pro

Spirited Away

2001

Kind of Blue

Miles Davis

The Left Hand of Darkness

Ursula K. Le Guin

Kyoto

Japan

Tetris (1984)

Puzzle

Qwen3.5 FlashQwen3.5 Flash

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

Neuromancer

William Gibson

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

GPT-5.2 Pro and Qwen3.5 Flash compared across 44 shared prompts
SpecGPT-5.2 ProQwen3.5 Flash
Input price$21/M tokens$0.1/M tokens
Output price$168/M tokens$0.4/M tokens
Context window400K tokens1.0M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedDec 2025Feb 2026
At 10M a month$210$210$1.00$1.00
1M10M100M1B10M tokens

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

Where to run it2 hosts
GPT-5.2 Pro1 host
HostInOutContextUptime
  • OpenAI$21.00 in·$168.00 out·400k·100% up
Qwen3.5 Flash1 host
HostInOutContextUptime
  • Alibaba Cloud$0.07 in·$0.26 out·1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.

Common questions

What is the difference between GPT-5.2 Pro and Qwen3.5 Flash?

GPT-5.2 Pro is developed by OpenAI while Qwen3.5 Flash is developed by Qwen. GPT-5.2 Pro has a 400K token context window vs Qwen3.5 Flash's 1.0M. You can compare their actual outputs across 44 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.2 Pro or Qwen3.5 Flash?

It depends on your use case. GPT-5.2 Pro and Qwen3.5 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 44 challenges so you can judge which fits your needs best.

How much does GPT-5.2 Pro cost compared to Qwen3.5 Flash?

GPT-5.2 Pro costs $21/M input tokens and Qwen3.5 Flash costs $0.1/M input tokens. Qwen3.5 Flash is $20.90/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-5.2 Pro and Qwen3.5 Flash on Rival?

This page shows a side-by-side comparison of GPT-5.2 Pro and Qwen3.5 Flash 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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  • Qwen3.5 Flash66 outputs, specs and price
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