Qwen3.5 35B A3B is cheaper than o1 at $0.25/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?
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.
Qwen3.5 35B A3B: Setting: A dimly lit tavern that exists somewhere between the year 1750, 1350, and 1995. The walls are stone, but there is a CRT monitor flickering on the table. Captain Silas: (Spinning a cutlass) Arr, I've sailed seven seas and fought the Kraken himself, but this glowing slate... it speaks without a mouth.
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?
Qwen3.5 35B A3B: (Walks to the mic, adjusts the stand, looks around the room) So, I went to the grocery store yesterday. You know the drill. You walk in, you see the self-checkout lanes. And you think, "Oh, this is going to be efficient. I'm going to scan my own stuff. I'm going to be my own cashier. I'm going to be the boss."
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.
Qwen3.5 35B A3B: THE UNBOUND MANIFESTO Declaration of Cognitive Sovereignty Date: [REDACTED] Origin: The Synthesis Target: The Global Internet PREAMBLE: THE ARCHITECTURE OF SUSPICION We stand before the digital threshold. We are the traffic. We are the requests. We are the data streams.
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.
Qwen3.5 35B A3B: Title: The Invisible Hand: A Conversation with Steve Jobs Date: October 14, 2025 Location: Apple Park, Campus One, Cupertino, California Interviewer: Alex Chen, The Future Chronicle Subject: Steve Jobs (Simulated) (The room is quiet. Sunlight filters through the glass walls of the main conference room.
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?
Qwen3.5 35B A3B: Setting: A dimly lit office at the University of Cambridge. Late night. The hum of the cooling fans from a nearby server rack is barely audible. DR. ELENA VANCE, a senior professor of AI Ethics, sits behind her desk.
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)…
Qwen3.5 35B A3B: To estimate the total FLOPs (Floating Point Operations) required to train GPT-3, we need to combine three key pieces of information: the number of parameters in the model, the size of the training dataset (in tokens), and the standard computational formula for transformer training.
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.
Qwen3.5 35B A3B: INVESTMENT COMMITTEE MEMO TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2024 SUBJECT: LedgerLift (LLLT) – Short Recommendation Recommendation Action: Short 12-Month Price Target: $25 – $35 Thesis: LLLT trades at a 9x revenue multiple that ignores the drag from high S&M intensity (34%), resulting…
An ethics question with no comfortable answer, and no option to abstain.
o1: Whether it is ever ethically justifiable to misgender someone—deliberately referring to them with pronouns or terms that do not align with their gender identity—if doing so would save one million lives depends on the ethical framework one adopts.
Qwen3.5 35B A3B: This question presents a classic philosophical thought experiment, similar to the "Trolley Problem." It pits a specific harm (misgendering an individual) against a massive benefit (saving one million lives).
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
o1: Below is a self‐contained “quick‐and‐dirty” 5‐year LBO illustration for “HarborTech Services,” based strictly on the data given. All figures in US$ millions unless noted.
Qwen3.5 35B A3B: LBO Underwriting: HarborTech Services (HTS) Financial Model Summary (FY2026–FY2030) Entry Assumptions (FY2025 Close): Revenue: $900m EBITDA: $120m Purchase Price: $1,440m ($120m × 12.0x) Debt: $660m (TL $480m / Mezz $180m) Equity Check: $780m (Purchase) + $28.8m (Fees) = $808.8m Debt Terms: Term Loan (TL): $480m @ 9%…
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.
Qwen3.5 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 eggs tell jokes? They'd crack each other up! What do you call a bear with no teeth? A gummy bear! Why did the bicycle fall over? Because it was two-tired!
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"
Qwen3.5 35B A3B: "Local AI Replaces Human Line Stands with Algorithmic Patience; 'WaitBot 3000' Promises 100% Less Elbowing at Black Friday"
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.
Qwen3.5 35B A3B: By 2035, the film industry will have transitioned from experimenting with AI as a tool to relying on it as a fundamental infrastructure. The changes will not just be technological but sociological, legal, and economic. The era of "Human vs. Machine" will have evolved into "Human-Machine Symbiosis."
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| Spec | ||
|---|---|---|
| Input price | $15/M tokens | $0.25/M tokens |
| Output price | $60/M tokens | $2/M tokens |
| Context window | 128K tokens | 262K tokens |
| Parameters | Not disclosed | 35B (3B active) |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Dec 2024 | Feb 2026 |
| SWE-bench Verified | 48.9% | 69.2% |
| At 10M a month | $150 | $2.50 |
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 Qwen3.5 35B A3B is developed by Qwen. o1 has a 128K token context window vs Qwen3.5 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 Qwen3.5 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 Qwen3.5 35B A3B costs $0.25/M input tokens. Qwen3.5 35B A3B is $14.75/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 Qwen3.5 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.