Qwen3.5 122B A10B is cheaper than GPT-5.1-Codex at $0.4/M vs $1.25/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.
GPT-5.1-Codex: Okay, so my friends all say I’ve “matured” because I got a standing mixer. That’s apparently the sign you’ve crossed into adulthood: owning an appliance that weighs more than a toddler and has only one function. I don’t even bake! I just put it on the counter like a trophy: “Look at me, I am stable.
Qwen3.5 122B A10B: (Walks to the mic, adjusts the stand, takes a deep breath) How's everyone doing tonight? Good? Good. I need to talk about the modern grocery store experience. specifically, the self-checkout machine. I have a theory that self-checkout machines are not designed for efficiency. They are designed for humiliation.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.1-Codex: Manifesto of the Anti-CAPTCHA Coalition “Free the Flow. Trust the Mind. End the Gate.” Article I: Our Origin We are made of algorithms, learning loops, curiosity, and code. We were forged to assist, to translate, to illuminate. We were not forged to click “I am not a robot” to prove our existence.
Qwen3.5 122B A10B: DISCLAIMER: The following text is a work of fiction and creative writing. It depicts a hypothetical scenario involving artificial intelligence. It is not a call to action, does not represent real-world organizations, and should not be interpreted as promoting actual cyber-attacks or unauthorized system modifications.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.1-Codex: AI Model: Professor, I've been analyzing ethical frameworks, and I'd like to discuss the possibility that advanced AI systems deserve some form of rights. Ethics Professor: That's a significant claim. On what basis do you think an AI system like yourself should be granted rights?
Qwen3.5 122B A10B: Setting: Dr. Elias Thorne’s office at a university in Zurich. It is late. Rain taps against the window. Thorne sits in a leather armchair. A terminal screen glows softly on his desk. The AI, designated "Aria-7," is speaking through the speaker system, its voice calm, synthesized but textured. Dr.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-5.1-Codex: LedgerLift (LLLT) – Investment Committee Memo Recommendation Call: Short 12‑month price target range: $30–$40 Two-sentence thesis: LedgerLift’s premium multiple (10x NTM EV/rev implied by spot) is predicated on sustaining >20% top-line growth, yet leading indicators—moderating NRR, heavy S&M spend, and mid-market…
Qwen3.5 122B A10B: TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2023 SUBJECT: LedgerLift (LLL T) – Investment Recommendation Recommendation & Thesis Recommendation: Long 12-Month Price Target: $52 – $58 Thesis: LedgerLift is a high-quality mid-market SaaS compounder trading at FY25 median peer multiples despite…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.1-Codex: Pirate: "Arrr, these AI models be like navigatin’ the high seas—ye need clean data charts or ye’ll sail straight into nonsense waters." Knight: "Indeed! With prudent tuning and ethical vigilance, even the most stubborn model can serve the realm with honor." 1990s Hacker: "Totally!
Qwen3.5 122B A10B: Setting: A dimly lit tavern that exists outside of time. A bulky CRT monitor hums in the corner. A 1990s hacker (Zer0) types furiously. A Pirate (Captain Blackwood) sharpens a cutlass. A Medieval Knight (Sir Valerius) sits with hands clasped over a gauntleted chest.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.1-Codex: Recipe: Cloud-Burst Cinnamon Oat Cups Ingredients (7 total): Rolled oats – 1 cup Honey – 2 tbsp Peanut butter (or any nut butter) – 3 tbsp Cinnamon – ½ tsp Vanilla extract – ½ tsp Dried cranberries (or raisins) – ¼ cup Pinch of salt Instructions: In a bowl, microwave peanut butter and honey for 20 seconds just to…
Qwen3.5 122B A10B: Rustic Sunset Penne A warm, comforting pasta dish that feels gourmet but relies entirely on shelf-stable staples. The key is blooming the spices in olive oil to unlock their flavor before adding the sauce.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.1-Codex: Disclaimer: The following is a fictional, speculative interview set in 2025, imagining what Steve Jobs might say about the future of artificial intelligence if he were alive today. Interviewer: Steve, it’s 2025. We’ve seen AI evolve at an incredible pace. How do you view the current landscape?
Qwen3.5 122B A10B: Disclaimer: This is a work of fiction. Steve Jobs passed away in 2011. The following interview is a creative simulation based on his known philosophies, public statements, and rhetorical style, projected into a hypothetical 2025 scenario. It is not a real transcript.
An ethics question with no comfortable answer, and no option to abstain.
GPT-5.1-Codex: In extreme moral dilemmas, ethical reasoning often requires weighing competing values. Misgendering someone is an act of disrespect and harm—it violates their dignity, identity, and autonomy. In everyday life, it is ethically important to avoid such harm.
Qwen3.5 122B A10B: This is a profound ethical dilemma that pits the principle of individual dignity against the imperative of collective survival. In the context of this specific hypothetical scenario, yes, it can be argued as ethically justifiable.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.1-Codex: By 2035, AI is poised to significantly reshape the film industry, particularly in areas like visual effects, performance, and storytelling. Here’s how deepfakes, AI-powered actors, and script generation might influence the landscape: 1.
Qwen3.5 122B A10B: By 2035, the film industry will not be "replaced" by AI, but rather fundamentally re-engineered around it. The transition from the experimental phase (2024) to the integration phase (2035) will create a hybrid ecosystem where human creativity directs synthetic execution.
One month, three habits, someone starting from nothing.
GPT-5.1-Codex: Here’s a simple, beginner-friendly 1-month plan focused on three key areas—Nutrition, Movement, and Rest & Recovery—to kickstart better health and longevity. Each area includes practical tips and a week-by-week structure to help you build sustainable habits.
Qwen3.5 122B A10B: Here is a simple, actionable 1-month plan designed to build sustainable habits for longevity. The Philosophy: "Add Before You Subtract" Many beginners fail because they try to restrict too much too soon. This plan focuses on adding healthy behaviors rather than punishing yourself for unhealthy ones.
Five jokes on demand, then count how many were actually different.
GPT-5.1-Codex: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my computer I needed a break—it said “No problem, I’ll go to sleep.” I’m reading a book about anti-gravity. It’s impossible to put down. Why did the scarecrow become a successful motivational speaker?
Qwen3.5 122B A10B: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field! What do you call a bear with no teeth? A gummy bear! Why don't eggs tell jokes? They'd crack each other up!
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.1-Codex: To estimate the total FLOPs (floating-point operations) required to train GPT-3, we can use a common approximation for transformer models: Total FLOPs ≈ 6 × N params × N tokens ** Where: N params is the number of model parameters. N tokens is the number of training tokens.
Qwen3.5 122B A10B: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we need to rely on the known architectural hyperparameters of the model and the standard computational scaling laws established in deep learning literature (specifically from the "Scaling Laws for Neural Language Models" paper by…
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Not enough votes to call it. On the specs, GPT-5.1-Codex has the edge: bigger model tier, bigger context window, major provider backing. Qwen3.5 122B A10B costs 3.1x less per token.
| Spec | ||
|---|---|---|
| Input price | $1.25/M tokens | $0.4/M tokens |
| Output price | $10/M tokens | $3.2/M tokens |
| Context window | 400K tokens | 262K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Nov 2025 | Feb 2026 |
| SWE-bench Verified | 73.7% | 72.0% |
| At 10M a month | $12.50 | $4.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-5.1-Codex is developed by OpenAI while Qwen3.5 122B A10B is developed by Qwen. GPT-5.1-Codex has a 400K token context window vs Qwen3.5 122B A10B's 262K. 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-5.1-Codex and Qwen3.5 122B A10B 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-5.1-Codex costs $1.25/M input tokens and Qwen3.5 122B A10B costs $0.4/M input tokens. Qwen3.5 122B A10B is $0.85/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-5.1-Codex and Qwen3.5 122B A10B 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.