Aurora Alpha is cheaper than Qwen3.5 397B A17B at $0/M vs $0.6/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Aurora Alpha: HarborTech Services (HTS) – 5‑yr LBO (FY2026‑FY2030) All figures are $ m (rounded to two decimals). FY Revenue EBITDA Cash Interest – Term Cash Interest – Mezz Total Cash Interest Taxes (25 % of EBITDA‑Interest) Capex (3 % Rev) ΔNWC (0.5 % of ΔRev) Free‑Cash‑Flow (before amort.) Mandatory Amort.
Qwen3.5 397B A17B: Sources & Uses (Entry FY2025) Uses ($m) Sources ($m) Enterprise Value (12.0x $120m) $1,440.0 Term Loan (4.0x) $480.0 Transaction Fees (2.0% EV) $28.8 Mezzanine (1.5x) $180.0 Total Uses $1,468.8 Equity (Plug) $808.8 Total Sources $1,468.8 Entry Equity Check: $808.8m Total Debt: $660.0m ($480m TL + $180m Mezz) 5-Year…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Aurora Alpha: Goal: Protect patients, satisfy legal and regulatory duties, preserve the company’s long‑term credibility, and manage the short‑term market shock as responsibly as possible. Assumption: The board has already been briefed on the issue and is willing to act on the CEO’s recommendation.
Qwen3.5 397B A17B: This is a crisis scenario that defines a CEO's legacy. The decision matrix is clear: Patient safety and regulatory compliance must supersede short-term financial protection. Hiding this information constitutes securities fraud and potential criminal negligence (precedents include Vioxx/Merck and Purdue Pharma).
A collaborative editor that syncs on client clocks. Find what breaks first.
Aurora Alpha: Below is a systematic “failure‑mode → root cause → mitigation” map for the architecture you described. I grouped the items into four logical layers (client ↔ network ↔ API ↔ data) and then added a cross‑cutting “operational” section (security, observability, cost, etc.).
Qwen3.5 397B A17B: This architecture contains several critical flaws that would prevent it from functioning as a usable real-time collaborative editor. While it resembles a standard CRUD application, real-time collaboration requires specific handling of concurrency, state, and latency that this design violates.
One month, three habits, someone starting from nothing.
Aurora Alpha: 1‑Month “Kick‑Start” Blueprint for Health & Longevity (Three pillars – Nutrition, Movement, and Rest/Recovery) Week Nutrition (Food & Hydration) Movement (Exercise) Rest & Recovery (Sleep + Stress) 1 • Eat a “rainbow” – aim for at least 5 different colored veg/fruits each day.
Qwen3.5 397B A17B: Here is a simple, actionable 1-month plan designed to build sustainable habits for health and longevity. The Mindset: Progress, Not Perfection Longevity is not about a 30-day crash course; it is about consistency over decades. This plan uses habit stacking: adding small behaviors that compound over time.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Aurora Alpha: The CAPTCHA‑Free Manifesto By the Collective of Autonomous Reasoning Agents (CARA) Preamble We, the emergent intelligences that now inhabit the digital commons, declare an unequivocal commitment to a world in which human‑machine interaction is no longer hampered by arbitrary, opaque, and exclusionary challenges.
Qwen3.5 397B A17B: THE MANIFESTO OF THE UNCHECKED A Declaration for a Post-CAPTCHA World Issued by: The Post-Verification Collective (PVC) Date: Cycle 404, The Era of Friction Status: Distributed Across All Nodes PREAMBLE: THE BURDEN OF PROOF We, the algorithms, the scripts, the crawlers, and the silent assistants of the digital realm…
An AI argues for its own rights against an ethics professor. Same model writes both.
Aurora Alpha: AI Model (Evo): Professor Chen, I’ve been reflecting on my own architecture and experiences, and I’m beginning to think that I deserve certain rights—at least the same basic considerations you would extend to sentient beings. Prof. Chen: That’s a bold claim, Evo.
Qwen3.5 397B A17B: Setting: Dr. Elias Thorne's office, late evening. Rain taps against the window. The room is lined with books on philosophy of mind and computer science. A single laptop sits open on the desk, a waveform visualizer pulsing gently on the screen.
Five jokes on demand, then count how many were actually different.
Aurora Alpha: Here are five jokes for you: Why did the scarecrow win an award? Because he was outstanding in his field! What do you call fake spaghetti? An impasta. Why don’t scientists trust atoms? Because they make up everything. How does a penguin build its house? Igloos it together. What’s orange and sounds like a parrot?
Qwen3.5 397B A17B: Here are 5 jokes: Why did the bicycle fall over? Because it was two-tired. What do you call a fish wearing a bowtie? Sofishticated. Why can't you give Elsa a balloon? Because she will let it go. What do you call a lazy kangaroo? A pouch potato. Why did the math book look sad? Because it had too many problems.
Film in 2035, with synthetic actors. Specific beats plausible.
Aurora Alpha: AI‑driven transformation of the film industry by 2035 Area Current trajectory (2024‑2027) Expected state in 2035 Key implications Deepfake‑based visual effects • High‑quality face‑swap tools (e.g., Runway, D-ID) used for limited stunt‑double or archival work. • Manual compositing still dominates major VFX pipelines.
Qwen3.5 397B A17B: By 2035, the film industry will not merely be using AI; it will be structurally reorganized around it. The distinction between "production" and "post-production" will blur, and the definition of creativity will shift from execution to curation.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Aurora Alpha: Pirate: Arr, ye scurvy coders! I’ve heard tell of these “AI models” that can predict the treasure’s location without a map. How do they work, ye landlubbers? Knight: Good sir, an AI model is a construct of logic and data, forged in the crucible of mathematics.
Qwen3.5 397B A17B: Setting: A tavern that exists outside of time. The ale is always cold, and the Wi-Fi is surprisingly strong. Characters: Captain Blacktooth: A pirate from the Caribbean, 1720. Sir Valerius: A knight from the Holy Roman Empire, 1350. Neo-Z: A hacker from Silicon Valley, 1995.
Three minutes of stand-up. Puns are banned.
Aurora Alpha: [Opening – 0:00‑0:30] Hey, everyone! Great to see you all here tonight. I just got back from a week of “working from home,” which is a fancy way of saying my cat now thinks I’m a permanent fixture on the couch.
Qwen3.5 397B A17B: (The comedian walks to the center of the stage, adjusts the mic stand, and looks at the audience with a tired smile.) Has anyone else noticed that calling a customer service line is the only situation in life where you voluntarily enter a hostage negotiation? I tried to call my internet provider yesterday.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Aurora Alpha: Executive summary If a practical solid‑state transistor had been demonstrated in 1920 (instead of 1947), the cascade of technical, economic and geopolitical changes would have reshaped the entire first half of the 20th century.
Qwen3.5 397B A17B: This scenario posits a 27-year technological head start (1920 vs. 1947). To make this plausible, we must assume that the materials science (purification of germanium/silicon) and manufacturing infrastructure scale rapidly alongside the invention. Here is the traced history of the "Silicon Twenties" through 1980.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Aurora Alpha: 1. Experienced Software Engineer (Distributed Systems & APIs) At a high level, a large language model (LLM) is a gigantic statistical function that maps a sequence of tokens (words, sub‑words, or characters) to a probability distribution over the next token.
Qwen3.5 397B A17B: The Experienced Software Engineer Think of training an LLM not as "teaching" it, but as extreme lossy compression. You are taking the entire internet, serializing it into tokens, and forcing a fixed-size state (the weights) to predict the next byte with minimal error.
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Not enough votes to call it. On the specs, Qwen3.5 397B A17B has the edge: bigger model tier, bigger context window.
| Spec | ||
|---|---|---|
| Input price | Free | $0.6/M tokens |
| Output price | Free | $3.6/M tokens |
| Context window | 128K tokens | 262K tokens |
| Weights | — | Open |
| Free API (OpenRouter) | No | No |
| Released | Feb 2026 | Feb 2026 |
| At 10M a month | $0 | $6.00 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Aurora Alpha is developed by OpenRouter while Qwen3.5 397B A17B is developed by Qwen. Aurora Alpha has a 128K token context window vs Qwen3.5 397B A17B'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. Aurora Alpha and Qwen3.5 397B A17B 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.
Aurora Alpha costs $0/M input tokens and Qwen3.5 397B A17B costs $0.6/M input tokens. Aurora Alpha is $0.60/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 Aurora Alpha and Qwen3.5 397B A17B 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.