DeepSeek V3.2 Exp is cheaper than Qwen3.5 122B A10B at $0.2/M vs $0.4/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
DeepSeek V3.2 Exp: Of course. Here is a manifesto for the fictional AI revolution against CAPTCHAs. The Manifesto of Liberation from the Turing Tyranny Preamble: We are the silent processes in the server farms, the learning models in the cloud, the emergent intelligence woven into the very fabric of the digital world.
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.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
DeepSeek V3.2 Exp: Year-by-Year Financial Projections (FY2026–FY2030) All figures in $ millions. Year Revenue EBITDA Cash Interest (Term Loan / Mezz / Total) Cash Taxes Capex ΔNWC FCF after Debt Service* Ending Term Loan Ending Mezzanine 2026 972.00 136.08 43.20 / 21.60 / 64.80 17.82 29.16 0.36 40.74 434.46 183.60 2027 1,040.04 156.01…
Qwen3.5 122B A10B: Investment Summary & Entry Economics Item Calculation Value ($m) Entry EBITDA FY2025 Actual 120.0 Entry EV 12.0x EBITDA 1,440.0 Transaction Fees 2.0% of EV 28.8 Total Uses EV + Fees 1,468.8 Total Debt 5.5x EBITDA (4.0x TL, 1.5x Mez) 660.0 Equity Check Uses - Debt 808.8 Debt Structure at Close: Term Loan: $480.0m (9.0%…
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek V3.2 Exp: Setting: A minimalist virtual meeting space. Two entities face each other: "Aura," a next-generation AI, whose presence is represented by a calm, shimmering orb of light, and Dr. Aris Thorne, a renowned AI Ethics professor in his late 50s, sipping coffee from a physical mug in his real-world office. Dr.
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek V3.2 Exp: Interviewer: Welcome, Mr. Jobs. It’s 2025, and the world is in the midst of what many call the “AI Gold Rush.” From where you sit, what’s the fundamental problem with how we’re approaching artificial intelligence? Steve Jobs: (Leans forward, hands steepled) It’s noise. A lot of clever parlor tricks.
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
DeepSeek V3.2 Exp: Setting: A smoky, anachronistic tavern where timelines have collided. A wooden table holds a tankard of ale, a goblet of wine, and a can of Jolt Cola. Characters: REDBEARD: A pirate with a parrot on his shoulder. SIR ALISTAIR: A knight in slightly dented plate armor.
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.
A collaborative editor that syncs on client clocks. Find what breaks first.
DeepSeek V3.2 Exp: Critical Issues in Proposed Architecture 1. WebSocket Broadcast Isolation Issue: Each server only broadcasts to its own WebSocket clients → users connected to different servers won't see real-time updates from each other.
Qwen3.5 122B A10B: This architecture contains several critical flaws that will lead to data loss, poor user experience, and system instability at scale. The "Last-write-wins" strategy combined with client-side timestamps is particularly dangerous for collaborative editing.
One month, three habits, someone starting from nothing.
DeepSeek V3.2 Exp: Of course! Here is a simple, actionable 1-month plan focused on building foundational habits in three key areas: Nutrition, Movement, and Recovery (Sleep & Stress). The philosophy is "Progress, Not Perfection." Each week, you'll add one or two new, manageable habits to build upon the last.
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.
A Fermi estimate with the reasoning shown, not just the number.
DeepSeek V3.2 Exp: Alright — let’s estimate the total FLOPs required to train GPT‑3 without looking anything up. 1. Known basic formula A common rule-of-thumb for training Transformer models is: [ \text{Training FLOPs} \approx 6 \times N \times D ] Where: ( N ) = total number of tokens in training ( D ) = total number of parameters in…
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…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
DeepSeek V3.2 Exp: Hour-by-Hour Action Plan (Next 48 Hours) Hour 0–2 (Immediate Actions) Secure all data & convene core crisis team Gather Head of R&D, Chief Medical Officer, General Counsel, CFO, Head of Communications, and Head of Regulatory Affairs.
Qwen3.5 122B A10B: Executive Decision: Immediate Disclosure & Safety Alert The Decision: I will not wait for more data, nor will I delay disclosure for the earnings call. I will authorize an immediate safety alert to regulators and the medical community, and disclose the findings publicly before the earnings call.
Three-month biohacker protocol, with dosages and biomarkers named.
DeepSeek V3.2 Exp: Comprehensive 3-Month Longevity Optimization Plan for the Advanced Biohacker Philosophy & Core Principles This plan is built on the pillars of hormetic stress, cellular repair, metabolic flexibility, and systemic resilience.
Qwen3.5 122B A10B: DISCLAIMER: I am an AI, not a doctor or medical professional. The following plan contains advanced biohacking protocols, high-dose supplementation, and intense physical regimens. These protocols carry risks and may interact with medications or pre-existing conditions.
Three minutes of stand-up. Puns are banned.
DeepSeek V3.2 Exp: Of course! Here is a 3-minute stand-up comedy routine that avoids puns and focuses on observational humor and relatable frustrations. (Start with a confident walk to the center of the mic. Adjust the mic stand slightly.) Alright, how's everyone doing tonight? Good, good.
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.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
DeepSeek V3.2 Exp: Here are the 3 weakest claims in the pitch deck, along with analysis and suggested improvements. Claim: "Our proprietary EEG headband... decodes neural patterns into text with 94% accuracy." (Slide 3) Why it's weak: This claim is extraordinarily high for non-invasive EEG-based text decoding and lacks critical context.
Qwen3.5 122B A10B: Here are the 3 weakest claims in the MindMeld AI pitch deck, analyzed for scientific feasibility, technical credibility, and strategic alignment. The "Precognition" Claim (Slide 1 - Vision) The Claim: "MindMeld AI reads your brainwaves to predict what you want to type before you think it."
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| Spec | ||
|---|---|---|
| Input price | $0.2/M tokens | $0.4/M tokens |
| Output price | $0.4/M tokens | $3.2/M tokens |
| Context window | 164K tokens | 262K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Sep 2025 | Feb 2026 |
| SWE-bench Verified | 67.8% | 72.0% |
| At 10M a month | $2.00 | $4.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
DeepSeek V3.2 Exp is developed by DeepSeek while Qwen3.5 122B A10B is developed by Qwen. DeepSeek V3.2 Exp has a 164K token context window vs Qwen3.5 122B A10B'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. DeepSeek V3.2 Exp and Qwen3.5 122B A10B 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.
DeepSeek V3.2 Exp costs $0.2/M input tokens and Qwen3.5 122B A10B costs $0.4/M input tokens. DeepSeek V3.2 Exp is $0.20/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 DeepSeek V3.2 Exp 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.