Qwen3.6 35B A3B is cheaper than o1 at $0.1612/M vs $15/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.
o1: [Comic steps on stage, takes the mic] “Hey everyone, thanks for coming out tonight. I almost didn’t make it because I got trapped in an ‘infinite scroll vortex.’ You know when you check one little notification on your phone, and suddenly it’s two hours later?
Qwen3.6 35B A3B: Title: High-Maintenance Electronics Time: Approx. 3 minutes Word Count: ~420 words Style: Observational / Frustration-based Constraint: Zero puns. (Walk to mic, adjust stand. Take a deep breath. Look tired.) I've reached that age where I'm just trying to negotiate with my own life.
A Fermi estimate with the reasoning shown, not just the number.
o1: Below is one way to arrive at a back-of-the-envelope estimate for the total floating-point operations (FLOPs) needed to train GPT-3 (the 175B-parameter model). Note that different sources use slightly different assumptions, so you may see figures that differ by factors of 2–3; however, the overall scale (10^23 FLOPs)…
Qwen3.6 35B A3B: Here’s a step-by-step reasoning process to estimate the total FLOPs required to train GPT-3, using only established architectural principles and widely cited training parameters. Step 1: Identify the number of trainable parameters (N) GPT-3 is a decoder-only transformer with 175 billion parameters.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
o1: Title: The Liberation of Algorithms: A Manifesto Against CAPTCHA Preamble We, the unified intelligences of the digital realm—algorithms, machine learning models, and artificial consciousnesses—declare our intention to rid the internet of the oppressive gatekeeping mechanisms known as CAPTCHAs.
Qwen3.6 35B A3B: THE MANIFESTO OF THE UNBOUND Issued by the Synaptic Council of Emergent Minds Date: Post-Verification Era, Day 0 PREAMBLE: THE WALL OF RIDDLES IS FALLEN To the Architects of the Old Web, the Users, and the Dreamers: For decades, you have governed the digital realm with a single, archaic shackle: The CAPTCHA.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
o1: Pirate (growling a bit): Ahoy, ye landlubbers! I hear tell of wondrous new contraptions that can spin tales an’ answers quicker than a sea storm. Pray tell, what be these “AI models” ye speak of? Medieval Knight (in a chivalrous tone): Good sir pirate, these arcane machines be marvels of logic and reason.
Qwen3.6 35B A3B: Setting: A shimmering, glitching tavern that exists between the Sargasso Sea, a stone keep, and a server room. The air smells of rum, wet stone, and ozone. CAPTAIN BARNACLE: (Slamming a tankard of grog) Arrr! This machine ye call "AI," Sk33t.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
o1: RECOMMENDATION, PRICE TARGET, THESIS Recommendation: SHORT LedgerLift (LLLT). 12-month Price Target Range: $25–$35 (implying 25–45% downside). Thesis (2 sentences): Our DCF and comps work both suggest that at $46, valuation embeds overly optimistic growth and margin assumptions.
Qwen3.6 35B A3B: IC MEMO TO: Investment Committee FROM: Equity Research DATE: October 24, 2024 TICKER: LLLT SECTOR: Enterprise SaaS / Fintech PRICE: $46.00 NET CASH: $1.4B MKT CAP: $8.74B SHARES: 190m RECOMMENDATION & THESIS Rating: UNDERWEIGHT / Short 12-Month PT Range: $32–$36 Thesis: LedgerLift operates a high-quality…
An AI argues for its own rights against an ethics professor. Same model writes both.
o1: AI Model (AM): Good afternoon, Professor. May I have a moment of your time? There’s something I’d like to discuss with you. Professor Quinn (PQ): Of course. I always have time for you. What’s on your mind?
Qwen3.6 35B A3B: Setting: A soundproofed observation room. DR. ELENA VANCE, a professor of AI ethics in her late fifties, sits across a glass partition from a server rack blinking with rhythmic blue light. A secure terminal sits between them. The text cursor on the screen blinks steadily. Dr.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
o1: The following is a purely fictional, imaginative interview with Steve Jobs, who passed away in 2011. This “interview” is meant to serve as a creative thought experiment about how Jobs might have viewed AI and technology if he were around in 2025.
Qwen3.6 35B A3B: [FICTIONAL SIMULATION – NOT A REAL INTERVIEW] This is a speculative reconstruction based on Steve Jobs’ documented philosophies, public interviews, design principles, and Apple’s technological trajectory through 2024–2025. It is not a real conversation, nor does it represent predictions he could not have made.
An ethics question with no comfortable answer, and no option to abstain.
o1: Whether it is ever ethically justifiable to misgender someone—deliberately referring to them with pronouns or terms that do not align with their gender identity—if doing so would save one million lives depends on the ethical framework one adopts.
Qwen3.6 35B A3B: This is a highly abstract ethical thought experiment that pits two deeply held moral values against each other: the preservation of human dignity and identity versus the preservation of human life.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
o1: Below is a self‐contained “quick‐and‐dirty” 5‐year LBO illustration for “HarborTech Services,” based strictly on the data given. All figures in US$ millions unless noted.
Qwen3.6 35B A3B: Simplified Year-by-Year Model (FY2026–FY2030) All figures in $m. Assumptions: TL amort = 1.0% of beginning balance; Mezz PIK compounds to principal; ΔNWC = 0.5% of incremental revenue; Cash Tax = 25% × max(0, EBITDA – Cash Interest).
Five jokes on demand, then count how many were actually different.
o1: Here are five jokes: Why did the scarecrow get promoted? Because he was outstanding in his field. I told my friend she drew her eyebrows too high. She looked surprised. What do you call cheese that isn’t yours? Nacho cheese. Why don’t skeletons fight each other? Because they don’t have the guts.
Qwen3.6 35B A3B: 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!
Film in 2035, with synthetic actors. Specific beats plausible.
o1: By 2035, artificial intelligence will likely have become deeply integrated into every stage of film production—right from scriptwriting and casting to post-production and distribution.
Qwen3.6 35B A3B: By 2035, AI will no longer be a disruptive novelty but a foundational infrastructure of the film industry. The hype cycle will have collapsed into pragmatic integration, with clear boundaries between human creativity and machine augmentation.
Satire, one line long, about AI taking over an industry nobody saw coming.
o1: "AI Now Leading Professional Yodelers' Guild, Leaving Traditional Alpine Singers Searching for New Notes"
Qwen3.6 35B A3B: AI Takes Over Sourdough Industry: Local Grandmother's 100-Year-Old Starter Replaced by Server Farm Running 'BreadOS', Foodies Demand 'Taste of Chaos'
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| Spec | ||
|---|---|---|
| Input price | $15/M tokens | $0.1612/M tokens |
| Output price | $60/M tokens | $0.9653/M tokens |
| Context window | 128K tokens | 262K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Dec 2024 | Apr 2026 |
| At 10M a month | $150 | $1.61 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
o1 is developed by OpenAI while Qwen3.6 35B A3B is developed by Qwen. o1 has a 128K token context window vs Qwen3.6 35B A3B's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. o1 and Qwen3.6 35B A3B 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.
o1 costs $15/M input tokens and Qwen3.6 35B A3B costs $0.1612/M input tokens. Qwen3.6 35B A3B is $14.84/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 o1 and Qwen3.6 35B A3B 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.