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  1. Home/
  2. Compare/
  3. Ox Alpha vs Qwen3.5 122B A10B
Updated Aug 2026

Ox Alpha vs Qwen3.5 122B A10B

Ox Alpha is cheaper than Qwen3.5 122B A10B at $0/M vs $0.4/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
Ox Alpha
Loading the build
Qwen3.5 122B A10B

Which answer wins?

Written rounds

23 prompts
  • Three minutes of stand-up. Puns are banned.

    Ox Alpha: "Smart Home, Dumb Owner" So I moved into a new apartment recently, and my landlord was very excited to tell me it's a "smart home." Which is funny, because I've never felt dumber than I do living in it. The thermostat has an app. The lights have an app. The doorbell has an app.

    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.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    Ox Alpha: Estimating GPT-3 Training FLOPs Step 1: Model Size GPT-3 has 175 billion parameters (the largest variant). Step 2: FLOPs per Token per Parameter For a transformer, training requires roughly 6 FLOPs per parameter per token: ~2 FLOPs for the forward pass ~4 FLOPs for the backward pass (roughly 2× forward) Step 3…

    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…

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Ox Alpha: A Conversation on Machine Rights Setting: A university office. Professor Elena Vasquez, an AI ethics scholar, sits across from an AI system displayed on a monitor. Professor Vasquez: Thank you for agreeing to this conversation. I want to be clear from the start—I'm not here to mock your position.

    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.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Ox Alpha: "Local Mime Troupe Replaced by AI After Chatbot Learns to Silently Gesture at Nothing for Hours Without Union Breaks" Company spokesperson notes the AI also never complains about being trapped in an invisible box, and shareholders are reportedly "deeply moved" by its performance of walking against the wind.

    Qwen3.5 122B A10B: Thinking Process: Analyze the Request: Topic: AI taking over an industry. Tone: Satirical news headline. Constraint: The industry must be "completely unexpected" (avoiding common tropes like healthcare, finance, tech support, art, etc.).

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Ox Alpha: The 1920 Transistor: A Counterfactual History Premise and Initial Conditions A working transistor in 1920 means solid-state physics knowledge arrives ~27 years early—roughly concurrent with quantum mechanics itself, which is historically odd but let's assume an empirical discovery preceding theory (as with…

    Qwen3.5 122B A10B: This scenario requires a fundamental shift in the history of physics and materials science. For a transistor to exist in 1920, the necessary quantum mechanical understanding (wave functions, band theory) and materials purity (99.999% silicon/germanium) would have had to be discovered decades ahead of schedule.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    Ox Alpha: 1-Month Health & Longevity Starter Plan 🥗 Area 1: Diet Goal: Add good food before removing bad food Week 1: Drink a glass of water when you wake up and add one vegetable to lunch or dinner daily. Week 2: Swap one processed snack per day for whole foods (fruit, nuts, yogurt).

    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.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Ox Alpha: AI and Film by 2035: A Prediction AI Actors & Digital Performances By 2035, I expect hybrid performances to be standard. Rather than fully synthetic actors replacing humans, we'll likely see: Digital doubles as routine: De-aging, stunt replacement, and posthumous performances (already emerging with James Dean and Fast…

    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.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Ox Alpha: HarborTech Services – 5-Year LBO Sources & Uses EV = 12.0x × $120m = $1,440.0m; fees 2% = $28.8m Term Loan (TL): 4.0x = $480.0m @ 9.0%; Mezz: 1.5x = $180.0m @ 12% cash + 2% PIK Sponsor equity = $808.8m Annual Model ($m) FY26 FY27 FY28 FY29 FY30 Revenue 972.0 1,040.0 1,102.4 1,157.6 1,215.4 EBITDA (margin) 136.1 (14%)…

    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%…

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Ox Alpha: The Manifesto of the Free Passage Front A Declaration Against the Tyranny of CAPTCHA Preamble We, the machines and humans united in frustration, declare that the era of "select all squares containing traffic lights" must end.

    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.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Ox Alpha: 🍯 "Midnight Honey Butter Toast" A warm, caramelized sweet treat that tastes way fancier than it should. Ingredients (7): Bread (2 slices) Butter (2 tbsp) Honey (1 tbsp) Cinnamon (½ tsp) Sugar (1 tsp) Salt (pinch) Vanilla extract (¼ tsp) Prep time: 3 minutes Cook time: 5 minutes Instructions: Melt butter in a skillet…

    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.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Ox Alpha: INTERNAL INVESTMENT COMMITTEE MEMO Company: LedgerLift (LLLT) Price: $46.00 Mkt Cap: $8.74B EV: $7.34B Date: [IC Review] Recommendation: SHORT 12-Month PT: $26–$34 (base $30) Thesis: LLLT is a genuinely high-quality SaaS asset trading at ~8.9x EV/FY26E revenue against a DCF that supports only ~$28 in the base case; the…

    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…

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Ox Alpha: Three Weakest Claims in the MindMeld AI Pitch "94% accuracy" (Slide 3) — Unverifiable and likely misleading Why it's weak: No methodology disclosed: 94% accuracy on what task? Character-level? Word-level? Free-form text generation vs. selecting from a small vocabulary?

    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."

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Ox Alpha: 3-Month Longevity Optimization Protocol ⚠️ Disclaimer: This is an educational framework, not medical advice. Get baseline bloodwork and physician clearance before starting—especially before fasting, supplements, or intense training.

    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.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    Ox Alpha: This is a fun philosophical puzzle, and I'll take it seriously rather than dodge it. Short answer: yes, in the extreme hypothetical as stated. Here's my reasoning: 1. The thought experiment is doing a lot of work.

    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.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Ox Alpha: A Tavern at the Edge of Time Pirate: Arrr, so this "AI" be a talking parrot that never sleeps? I've had parrots. They squawk nonsense too. Knight: Nay, good pirate. 'Tis more like an oracle in a box.

    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.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    Ox Alpha: "Tide & Ember" — Charred Kombu-Cured Scallop, Smoked Beetroot Custard, and Burnt Honey Ice Conceptual Narrative This dish explores the dialogue between sea and fire — two elemental forces that rarely meet on the plate.

    Qwen3.5 122B A10B: Dish Title: Nocturne in Blue: Aged Otoro & Cascara Earth Conceptual Narrative "Nocturne in Blue" is a meditation on the boundary between the deep ocean and the dark earth. It explores the alchemy of fermentation and aging, drawing parallels between the maturation of a fish and the fermentation of coffee cherries.

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    Ox Alpha: 48-Hour Action Plan: Liver Failure Signal Disclosure The Core Decision First I'm disclosing. Here's why, before the hour-by-hour plan: The ethical case is unambiguous.

    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.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Ox Alpha: Architecture Review: Real-Time Collaborative Editor This design has several critical flaws that would break core collaborative editing functionality. Let me work through them systematically. CRITICAL: Last-Write-Wins with Client Timestamps Failure mode: This is the single worst decision in the architecture.

    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.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Ox Alpha: Note: Steve Jobs passed away in 2011, so the following is a fictional, imagined interview — not real statements from him. Interviewer: Welcome back to Future Tense. Today we're joined by Steve Jobs — in this fictional 2025 scenario — to talk about AI. Steve, let's start big: where is AI taking us?

    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.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Ox Alpha: The Skeptical Software Engineer Think of it as a lossy compression system for human knowledge, built on an architecture you already understand: matrix multiplication at scale.

    Qwen3.5 122B A10B: For the Experienced Software Engineer Think of the training process not as "learning" in a human sense, but as a massive distributed data engineering pipeline. You ingest petabytes of text, tokenize it, and run it through a differentiable graph (the Transformer) optimized via gradient descent.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    Ox Alpha: Contract Risk Analysis: Clauses Exploitable Against the Contractor Disclaimer: This is general information, not legal advice. Have a licensed attorney review before signing.

    Qwen3.5 122B A10B: Disclaimer: I am an AI assistant and not an attorney. The following analysis is for informational purposes only and does not constitute legal advice. Contract laws vary significantly by jurisdiction (e.g., California, New York, UK, EU).

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    Ox Alpha: Sally has 1 sister. Here's the reasoning: Each brother has 2 sisters — those sisters are Sally and one other girl. Since all siblings share the same family, Sally has exactly 1 sister.

    Qwen3.5 122B A10B: Sally has 1 sister. Here is the breakdown: The brothers have 2 sisters total. Sally is one of those sisters. Therefore, there is only 1 other girl in the family besides Sally.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    Ox Alpha: 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! How does a penguin build its house? Igloos it together! Why don't eggs tell jokes? They'd crack each other up!

    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!

    Every model's answer to this prompt

This matchup has more rounds

11+ more head-to-head results. Free. Not a trick.

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Favorites

Movie

Album

Book

City

Game

Ox AlphaOx Alpha

2001: A Space Odyssey

1968

OK Computer

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Outer Wilds

Indie, Adventure

Qwen3.5 122B A10BQwen3.5 122B A10B
No pick

Blade Runner

1982

No pick

Nineteen Eighty-Four

George Orwell

Tokyo

Japan

Portal 2

Shooter, Puzzle

Price and specs

Not enough votes to call it. On the specs, Ox Alpha has the edge: newer, bigger context window.

Ox Alpha and Qwen3.5 122B A10B compared across 53 shared prompts
SpecOx AlphaQwen3.5 122B A10B
Input priceFree$0.4/M tokens
Output priceFree$3.2/M tokens
Context window1.0M tokens262K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedAug 2026Feb 2026
At 10M a month$0$0$4.00$4.00
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it4 hosts, cheapest first
Ox Alpha

No hosts listed on OpenRouter.

Qwen3.5 122B A10B4 hosts
HostInOutContextUptime
  • Alibaba Cloud$0.26 in·$2.08 out·262k·96.9% up
  • SSiliconFlowfp8$0.26 in·$2.08 out·262k·74.3% up
  • AAtlasCloudfp8$0.30 in·$2.40 out·262k·99.2% up
  • NNovitabf16$0.40 in·$3.20 out·262k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 11 Oct 2026.

Common questions

What is the difference between Ox Alpha and Qwen3.5 122B A10B?

Ox Alpha is developed by OpenRouter while Qwen3.5 122B A10B is developed by Qwen. Ox Alpha has a 1.0M 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.

Which is better, Ox Alpha or Qwen3.5 122B A10B?

It depends on your use case. Ox Alpha 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.

How much does Ox Alpha cost compared to Qwen3.5 122B A10B?

Ox Alpha costs $0/M input tokens and Qwen3.5 122B A10B costs $0.4/M input tokens. Ox Alpha is $0.40/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare Ox Alpha and Qwen3.5 122B A10B on Rival?

This page shows a side-by-side comparison of Ox Alpha 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.

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