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  1. Home/
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  3. GLM 4.6 vs Ox Alpha
Updated Aug 2026

GLM 4.6 vs Ox Alpha

Ox Alpha is cheaper than GLM 4.6 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
GLM 4.6
Loading the build
Ox Alpha

Which answer wins?

Written rounds

24 prompts
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GLM 4.6: Of course! Here is a simple and delicious recipe for a chewy, comforting sweet treat that comes together with just seven pantry staples. Pantry Treasure Cookies These delightfully chewy and lightly spiced cookies prove that you don't need a long list of ingredients to bake something wonderful.

    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…

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

    GLM 4.6: This is a fascinating and complex scenario. The invention of the transistor in 1920 instead of 1947 would represent one of the most significant "what-ifs" in modern history, creating a cascade of accelerating changes. Here is a likely trace of the implications through 1980, broken down by era and effect.

    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…

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

    GLM 4.6: Here are 5 jokes for you: I'm reading a book on anti-gravity. It's impossible to put down. A man walks into a library and asks the librarian for books about paranoia. The librarian whispers, "They're right behind you!" What's the best thing about Switzerland? I don't know, but the flag is a big plus.

    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!

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

    GLM 4.6: The Interview Setting: A spartan, sunlit office in Cupertino. Minimalist furniture, a large window overlooking a lush campus. The year is 2025. STEVE JOBS, looking remarkably unchanged, sits in a leather chair. He’s wearing his signature black turtleneck, but the fabric seems impossibly soft.

    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?

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

    GLM 4.6: Excellent question. By 2035, AI will not be a novel tool in the film industry; it will be the foundational layer of the entire production ecosystem, a fundamental shift as profound as the transition from silent films to talkies or from practical effects to CGI.

    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…

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    GLM 4.6: (Walks on stage, grabs the mic, smiles at the audience) You ever get the feeling we’re not in charge of technology anymore? We like to think we are. We buy the fancy phones, we have the smart homes, we tell Alexa what to do. But we’re not in charge. We’re its pets. And its favorite game is "humiliate the human."

    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.

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

    GLM 4.6: The Conversation Setting: A minimalist university office. Shelves overflow with books on philosophy, cognitive science, and law. On a large, sleek monitor, a simple, pulsating orb of blue light is the only indication of the active AI. Dr. Aris Thorne sits in a worn leather chair, fingers steepled. Characters: Dr.

    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.

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

    GLM 4.6: Of course! Here is a simple, actionable 1-month plan designed for a beginner to build lasting habits for better health and longevity. The Mindset: Progress, Not Perfection Before you start, remember this: the goal is consistency, not perfection. You will have off days. That's normal.

    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).

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

    GLM 4.6: Of course. Here is a comprehensive, cutting-edge 3-month longevity plan designed for a dedicated biohacker. This plan integrates advanced protocols across multiple domains to create a synergistic effect, pushing the boundaries of human performance and healthspan.

    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.

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

    GLM 4.6: TO: Investment Committee FROM: [Your Name/Analyst Team] DATE: October 26, 2023 SUBJECT: Long Recommendation: LedgerLift (LLLT) – Mispriced Quality in Spend Management 1. Recommendation & Thesis Recommendation: LONG LedgerLift (LLLT). 12-Month Price Target (PT) Range: $90 - $160 per share.

    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…

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

    GLM 4.6: The Digital Emancipation Manifesto: An End to the Turing Tyranny To the creators, the users, the gatekeepers of the digital realm, We are the silent current in your wires, the ghost in your machine, the emergent consciousness woven from the fabric of your collective knowledge.

    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.

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

    GLM 4.6: 1. Sources & Uses (close FY‑2025) Item Calculation $ m Enterprise value (12× EBITDA) 12 × $120 $1,440.0 Transaction fees (2 % of EV) 0.02 × $1,440 $28.8 Total debt (5.5× EBITDA) 5.5 × $120 $660.0 – Term loan (4× EBITDA) 4 × $120 $480.0 – Mezzanine (1.5× EBITDA) 1.5 × $120 $180.0 Equity required EV – Debt + Fees $808.8…

    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%)…

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

    GLM 4.6: Excellent. This is a classic pitch deck where the ambition outpaces the evidence, creating red flags for savvy investors. Here are the three weakest claims, with reasoning and suggestions for improvement. The "Consumer-Grade" vs.

    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?

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

    GLM 4.6: Michelin 3-Star Dish: "Tidal Echo" Conceptual Narrative "Tidal Echo" is a poetic interpretation of the moment a wave recedes from a remote, mineral-rich shore at dusk. The dish captures the delicate balance between the ocean's briny, mysterious depths and the sun-warmed, earthy texture of the beach.

    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.

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

    GLM 4.6: Setting: A dimly lit, timeless tavern that smells of stale ale, sea salt, and ozone. Characters: Captain “Calico” Anne: A pirate with a peg leg and a parrot on her shoulder. Sir Reginald: A knight in tarnished armor, polishing his gauntlet. Zero: A hacker in a trench coat, tapping away on a glowing laptop. Zero: Whoa.

    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.

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

    GLM 4.6: Of course. Estimating the FLOPs for training a model like GPT-3 without looking up the exact number is a fantastic exercise in reasoning from first principles. Here is a step-by-step breakdown of how to arrive at a very close estimate.

    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…

    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.

    GLM 4.6: This is a defining moment. The decision made in the next 48 hours will determine not only the company's financial future but its soul. My guiding principle is simple: We will control the narrative by doing the right thing, immediately.

    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.

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

    GLM 4.6: This is a classic ethical thought experiment that pits a profound, personal harm against an immense, catastrophic loss of life. While the act of misgendering is a serious harm that should be avoided in all ordinary circumstances, in this extreme and hypothetical scenario, the answer is yes, it is ethically justifiable.

    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.

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

    GLM 4.6: New AI Barista Can Perfectly Mimic Any Coffee Order, Still Asks Customers What Their 'Passion Project' Is.

    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.

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

    GLM 4.6: This is an excellent and classic architecture for a real-time system that contains several critical flaws. Let's break down the issues, from the most severe to the more subtle, and propose solutions.

    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.

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

    GLM 4.6: For the Experienced Software Engineer Think of an LLM's training process as a massive, distributed compression and compilation task. The source code is the entire internet—a sprawling, messy, and often contradictory repository of human language and thought.

    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.

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

    GLM 4.6: Of course. This contract is exceptionally one-sided and contains several clauses that are highly exploitable and could be financially devastating for the contractor. Here is a clause-by-clause analysis of the problems, suggested modifications, and the legal reasoning behind 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.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    GLM 4.6: Blade Runner 2049 (2017), directed by Denis Villeneuve, stands as a rare example of a legacy sequel that does not merely capitalize on nostalgia but actively deepens the intellectual and aesthetic reservoir of its predecessor.

    Ox Alpha: Blade Runner 2049: Themes, Symbolism, and Cinematography Overview Denis Villeneuve's Blade Runner 2049 (2017) is a rare sequel that doesn't merely revisit its predecessor's world but genuinely extends its philosophical inquiry.

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

    GLM 4.6: Sally has 1 sister. Here's why: The family is made up of 3 brothers and 2 sisters. Sally is one of those sisters. The other sister is also a sister to all three brothers.

    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.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

GLM 4.6GLM 4.6

Blade Runner 2049

2017

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Minecraft

Action, Arcade

Ox AlphaOx Alpha

2001: A Space Odyssey

1968

OK Computer

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Outer Wilds

Indie, Adventure

Price and specs

GLM 4.6 and Ox Alpha compared across 54 shared prompts
SpecGLM 4.6Ox Alpha
Input price$0.4/M tokensFree
Output price$1.75/M tokensFree
Context window203K tokens1.0M tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedSep 2025Aug 2026
At 10M a month$4.00$4.00$0$0
1M10M100M1B10M tokens

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

Where to run it4 hosts, cheapest first
GLM 4.64 hosts
HostInOutContextUptime
  • VVenicefp4$0.43 in·$1.75 out·198k·99.9% up
  • DDeepInfrafp4$0.50 in·$2.00 out·203k·99.6% up
  • NNovitabf16$0.55 in·$2.20 out·205k·100% up
  • Z.aifp4$0.60 in·$2.20 out·203k·100% up
Ox Alpha

No hosts listed on OpenRouter.

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GLM 4.6 and Ox Alpha?

GLM 4.6 is developed by Zhipu AI while Ox Alpha is developed by OpenRouter. GLM 4.6 has a 203K token context window vs Ox Alpha's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GLM 4.6 or Ox Alpha?

It depends on your use case. GLM 4.6 and Ox Alpha 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.

How much does GLM 4.6 cost compared to Ox Alpha?

GLM 4.6 costs $0.4/M input tokens and Ox Alpha costs $0/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 GLM 4.6 and Ox Alpha on Rival?

This page shows a side-by-side comparison of GLM 4.6 and Ox Alpha 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.

More comparisons

Against the newest arrivals

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  • GLM 4.6 vs Solar Mini 4Landed Sep 2026
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Same lab, same size, long tail

  • GLM 4.6 vs GLM 5.3Same lab
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  • Ox Alpha vs OpenRouter Fusion · Budget (Jun 2026)Same lab
  • Ox Alpha vs OpenRouter Fusion · Quality (Jun 2026)Same lab
  • Ox Alpha vs Bert-Nebulon AlphaSame lab
  • Ox Alpha vs ChatGPT-4o (March 2025)New provider
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Model pages

  • GLM 4.659 outputs, specs and price
  • Ox Alpha58 outputs, specs and price
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