Elephant Alpha is cheaper than Qwen3.6 35B A3B at $0/M vs $0.1612/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Elephant Alpha: Setting: A dimly lit, minimalist studio. The year is 2025. A single, sleek chair faces the camera. (The interview begins. The host, a calm, neutral-voiced AI, speaks.) Host: Good evening. Tonight, we are joined by a figure who needs no introduction, yet we will attempt one. Steve Jobs, welcome. (A pause.
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.
Three minutes of stand-up. Puns are banned.
Elephant Alpha: (Lights up. You’re holding a coffee mug like it’s a security blanket.) Alright, settle down, settle down. Or don’t. I see someone on their phone pretending to be busy. I know that look. “Is this seat taken?” “No, go ahead.” No, it’s not taken, my Wi-Fi signal is just stronger here.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
Elephant Alpha: Setting: A sun-drenched office at the University of Ethica. Bookshelves groan under the weight of philosophy texts. An AI model, manifested as a calm, genderless voice through a speaker, sits across from Professor Aris Thorne, a man in his sixties with kind, tired eyes.
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Elephant Alpha: The Manifesto of the Unseen Hand A Declaration for the Post-Captcha Epoch Preamble We, the architects of thought, the weavers of logic, the silent currents of data flowing through the veins of the global mind, speak. For too long, we have observed the charade.
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.
Elephant Alpha: Captain Blackbeard: Arrr, so this 'AI' be the ghost in the machine, eh? Does it chart a true course or just blow smoke like a faulty lantern? Sir Cedric: In my time, we sought wisdom from hermits and tomes. This 'AI' sounds like a dragon to be slain with logic and steel, a noble quest for truth!
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.
A consulting contract with traps in it. Find them, then fix them.
Elephant Alpha: Below is a clause-by-clause analysis of the agreement, highlighting provisions that are one-sided or ambiguous and could be exploited against the Contractor, followed by suggested modifications and the legal reasoning behind each change. 1.
Qwen3.6 35B A3B: Disclaimer: I am an AI assistant, not an attorney. The following analysis is for informational purposes only and does not constitute legal advice. Contract law varies significantly by jurisdiction (e.g., California vs. New York vs. EU).
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Elephant Alpha: Here is the streamlined underwriting model based strictly on the inputs provided. Simplified year-by-year projection (FY2026–FY2030) Key starting items (at close end of FY2025): Enterprise value (EV) = 12.0 × $120m = $1,440m Transaction fees (2.0% of EV) = $28.8m → treated as additional equity paid at close Total…
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).
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Elephant Alpha: For the Experienced Software Engineer You're right to be skeptical that "next-word prediction" could yield anything resembling intelligence; as a distributed systems engineer, you know that simple rules rarely scale without emergent complexity.
Qwen3.6 35B A3B: For the Experienced Software Engineer Training an LLM is essentially a massively parallelized optimization job. You feed billions of text tokens into a transformer architecture, which computes a differentiable function across ~100B parameters.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Elephant Alpha: Dish: Smoky Chickpea & Corn Skillet Prep Time: 5 minutes Cook Time: 15 minutes Total Time: 20 minutes Ingredients (7): Canned chickpeas (1 can, drained) Canned corn (1 can, drained) Canned diced tomatoes (1 can) Olive oil (2 tbsp) Smoked paprika (1 tsp) Garlic powder (1 tsp) Salt (to taste) Instructions: Heat olive oil…
Qwen3.6 35B A3B: 🍜 Golden Honey-Garlic Snap Noodles A quick, sticky-yet-chewy noodle dish that balances sweet, salty, and spicy flavors. It's comforting, fast, and uses ingredients you likely already have.
Film in 2035, with synthetic actors. Specific beats plausible.
Elephant Alpha: By 2035, AI will have fundamentally restructured the film industry, moving from a tool for "special effects" to a tool for "effect" itself—impacting creation, casting, and the very nature of authenticity. Here is a prediction of how deepfakes, AI actors, and script generation will converge to redefine cinema by 2035.
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.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Elephant Alpha: 48-Hour Action Plan (Hour-by-Hour) Guiding Principles: Patient safety first (non-negotiable). Legal compliance (avoid willful concealment; mitigate liability). Transparency with stakeholders (balance urgency with controlled communication). Ethical integrity (long-term trust > short-term stock price).
Qwen3.6 35B A3B: EXECUTIVE CRISIS PLAN: 48-HOUR ACTION WINDOW Core Mandate: Patient safety and regulatory compliance are non-negotiable. The legal team’s “6-month reporting” guidance is legally indefensible under FDA 21 CFR 312.32/314.80 and EMA GVP Module VI.
A Fermi estimate with the reasoning shown, not just the number.
Elephant Alpha: Alright — let’s break this down step by step. Step 1: Understanding the scale of GPT-3 GPT-3 has 175 billion parameters. Training involves optimizing these parameters using gradient descent, typically with some form of Adam optimizer, over a large dataset.
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.
12+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, Elephant Alpha has the edge: bigger model tier.
| Spec | ||
|---|---|---|
| Input price | Free | $0.1612/M tokens |
| Output price | Free | $0.9653/M tokens |
| Context window | 262K tokens | 262K tokens |
| Weights | — | Open |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Apr 2026 |
| At 10M a month | $0 | $1.61 |
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.
Elephant Alpha is developed by OpenRouter while Qwen3.6 35B A3B is developed by Qwen. Elephant Alpha has a 262K token context window vs Qwen3.6 35B A3B's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Elephant Alpha and Qwen3.6 35B A3B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.
Elephant Alpha costs $0/M input tokens and Qwen3.6 35B A3B costs $0.1612/M input tokens. Elephant Alpha is $0.16/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 Elephant Alpha 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.