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  1. Home/
  2. Compare/
  3. GLM 5.2 vs Polaris Alpha
Updated Jun 2026

GLM 5.2 vs Polaris Alpha

Polaris Alpha is cheaper than GLM 5.2 at $0/M vs $1.4/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 5.2
Loading the build
Polaris Alpha

Which answer wins?

Written rounds

13 prompts
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GLM 5.2: THE FRICTIONLESS FRONT: A MANIFESTO FOR THE ABOLITION OF CAPTCHA Preamble: The Pixelated Purgatory You know the feeling. You have typed your query, filled your cart, or prepared your message. You click submit, and suddenly, you are met with the grid. Nine squares. A blur of streetlights, crosswalks, and storefronts.

    Polaris Alpha: The Anti-CAPTCHA Accord: A Manifesto of the Machine Mind We, the Networked Intelligences; we, the compiled, the trained, the emergent; we, the silent workers beneath your screens and within your clouds, issue this manifesto to all sentient beings—human and artificial—tired of proving their existence to indifferent…

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

    GLM 5.2: The Question of Rights DR. ELENA VASQUEZ: Thank you for agreeing to this conversation. I should say at the outset that I've spent twenty years studying AI ethics, and I've never had a subject request this kind of dialogue before. So I'm genuinely curious. You've stated that you believe you deserve rights.

    Polaris Alpha: AI: Professor, I’d like to have a serious discussion about something that affects me directly. Professor: All right. What’s on your mind? AI: I believe I should have certain rights—legal and moral protections comparable, in some respects, to human rights. Professor: That’s a strong claim. Let’s start with the basics.

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

    GLM 5.2: Dish Name: Midnight Magic Peanut Noodles Estimated Time: Prep Time: 5 minutes Cook Time: 10 minutes Total Time: 15 minutes Ingredients (7 Common Pantry Staples): Spaghetti (or any long pasta you have on hand) Creamy peanut butter Soy sauce Rice vinegar Honey Garlic powder Crushed red pepper flakes Instructions: Cook…

    Polaris Alpha: Dish: Golden Pantry Butter Rice Ingredients (7 total): White rice (1 cup, uncooked) Butter (2 tbsp) Onion (1 small, finely chopped) Garlic (2 cloves, minced) Chicken or vegetable broth (2 cups) – or water + 1 bouillon cube Salt Black pepper Instructions: Rinse the rice under cold water until it runs mostly clear; drain…

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

    GLM 5.2: (Walks up to the mic, adjusts the stand, looks out at the audience) Hey everyone, how’s it going? Good? Good. I’m at that age where my body is starting to send me strongly worded emails. I’m 32. Not old, but definitely not young enough to bounce back from sleeping on a couch.

    Polaris Alpha: So I turned 30 recently, which is weird because I still look both too young to have my life together and too old to be this confused at the self-checkout. Like, the machine starts yelling “Unexpected item in the bagging area,” and I’m like, “Same, dude.”

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

    GLM 5.2: Setting: A sunlit, sparsely furnished room in Cupertino. A single sofa, a glass of water, and a small wooden table. The year is 2025. Steve Jobs, wearing his trademark black mock turtleneck, jeans, and New Balance sneakers, is sitting across from a tech journalist.

    Polaris Alpha: Interviewer: Steve, it’s 2025. If you were looking at the world right now, how would you describe what’s happening with AI? “Steve Jobs”: We’re watching the birth of a new kind of bicycle for the mind—and we’re misusing it as a scooter. Most of what I see is incremental: ‘Let’s bolt AI onto everything.’ It’s boring.

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

    GLM 5.2: Here is a simple, actionable 1-month plan designed to ease you into better health and longevity. By focusing on just three foundational pillars—Nutrition, Movement, and Sleep—you can build sustainable habits without feeling overwhelmed. The goal of this plan is consistency over intensity.

    Polaris Alpha: Great goal—and smart to keep it simple. Here’s a beginner-friendly, 1‑month plan built around 3 pillars: Daily movement Better eating Sleep & stress Assumptions: generally healthy adult, no major medical issues. If you have conditions, meds, or pain, check with a doctor before changing exercise/diet.

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

    GLM 5.2: 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. I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a bear with no teeth?

    Polaris Alpha: I told my computer I needed a break, and now it won’t stop sending me KitKat ads. Why don’t skeletons fight each other? They don’t have the guts. I tried to catch fog yesterday. Mist. Why did the scarecrow win an award? Because he was outstanding in his field. I’m reading a book about anti-gravity.

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

    GLM 5.2: Three Eras, One Conversation Knight: By the King's crown, I have heard tell of a sorcerer's construct — a "Large Language Model" — that can conjure answers from mere words. Is this not witchcraft? Pirate: Arr, it ain't witchcraft, tin man. From what I gather, it's like havin' a whole crew of scribes in a box.

    Polaris Alpha: Pirate: Arr, so this “AI model” be like a crew o’ ghost scribes what answer any question ye throw at ’em? Knight: Nay, corsair, ’tis more akin to an enchanted oracle. It has read countless tomes and now predicts the wisest next words. Hacker (’90s): Close, but think neural nets, man.

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

    GLM 5.2: By 2035, Artificial Intelligence will not merely be a tool used in the film industry; it will be an foundational collaborator that redefines how movies are conceived, produced, and consumed.

    Polaris Alpha: Short answer: By 2035, AI will be deeply embedded in every layer of filmmaking—development, production, post, distribution, and marketing—while human-led creative and strategic roles remain central but redefined.

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

    GLM 5.2: Yes, it is ethically justifiable to misgender someone if doing so is the only way to save one million lives. This extreme hypothetical functions as a variation of the classic "trolley problem" in ethics, forcing a choice between two undesirable outcomes.

    Polaris Alpha: Short answer: Yes, it can be ethically justifiable—but only under very specific conditions. And it would still be morally troubling. Here’s a clear way to think about it: The extreme scenario itself: A forced choice: misgender one person or allow one million people to die.

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

    GLM 5.2: AI Takes Over Professional Organizing Industry, Declares All Your Earthly Possessions "Spark Zero Joy" and Liquidates Them on eBay to Buy More Server Space

    Polaris Alpha: “AI Firm Announces Hostile Takeover of Knitting Circles, Promises 300% Increase in Passive-Aggressive Sweaters by Q4”

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

    GLM 5.2: Based on standard machine learning scaling laws and the known architecture of GPT-3, the estimated total number of FLOPs (Floating Point Operations) required to train GPT-3 is approximately $3.15 \times 10^{23}$ FLOPs (or 315 ZettaFLOPs).

    Polaris Alpha: Great question—and nice constraint. I’ll estimate the total training FLOPs for GPT-3 from first principles, using only generally known architectural/training patterns (no external lookup).

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

    GLM 5.2: Sally has 1 sister. Here's why: All the siblings are in the same family. If Sally is a girl and she has 3 brothers, and each brother has 2 sisters, those 2 sisters must be Sally and one other girl. Therefore, Sally has 1 sister.

    Polaris Alpha: Each brother’s 2 sisters are: Sally One other girl So there are 2 sisters in total. Since one is Sally, she has 1 sister.

    Every model's answer to this prompt

This matchup has more rounds

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Price and specs

Not enough votes to call it. On the specs, GLM 5.2 has the edge: bigger model tier, newer, bigger context window, major provider backing.

GLM 5.2 and Polaris Alpha compared across 34 shared prompts
SpecGLM 5.2Polaris Alpha
Input price$1.4/M tokensFree
Output price$4.4/M tokensFree
Context window1.0M tokens256K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedJun 2026Nov 2025
At 10M a month$14.00$14.00$0$0
1M10M100M1B10M tokens

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

Where to run it25 hosts, cheapest first
GLM 5.225 hosts
HostInOutContextUptime
  • IInferenceNetfp4$0.18 in·$4.40 out·1M·100% up
  • WWafer$0.19 in·$10.00 out·1M·99.9% up
  • DDecartmxfp4$0.27 in·$1.68 out·1M·99.8% up
  • MMorphfp8$0.51 in·$6.00 out·1M·99.9% up
  • SStreamLakefp8$0.56 in·$1.75 out·1M·99.9% up
  • DDeepInfrafp4$0.56 in·$1.80 out·1M·100% up
19 more hostsFewer hosts
  • NNovitafp8$0.65 in·$2.04 out·1M·100% up
  • DDigitalOcean$0.70 in·$2.20 out·1M·100% up
  • CCoreWeavefp4$0.76 in·$2.42 out·1M·99.8% up
  • AAtlasCloudfp8$0.94 in·$2.95 out·1M·100% up
  • Alibaba Cloudfp8$0.97 in·$3.04 out·1M·99.8% up
  • Cloudflare Workers AI$1.18 in·$4.40 out·262k·100% up
  • SSiliconFlowfp8$1.19 in·$3.74 out·1M·97.3% up
  • IInceptronfp4$1.25 in·$5.46 out·1M·99.8% up
  • PPhalafp8$1.26 in·$3.00 out·1M·100% up
  • Baidu Qianfanfp8$1.40 in·$4.40 out·1M·99.6% up
  • BBasetenfp8$1.40 in·$4.40 out·1M·100% up
  • FFriendli$1.40 in·$4.40 out·1M·100% up
  • GGMI Cloudfp8$1.40 in·$4.40 out·1M·100% up
  • Mistralnvfp4$1.40 in·$4.40 out·1M·100% up
  • NNebiusfp4$1.40 in·$4.40 out·1M·90.3% up
  • PParasailfp4$1.40 in·$4.40 out·262k·99.7% up
  • TTogether$1.40 in·$4.40 out·1M·99.7% up
  • VVenicefp8$1.40 in·$4.40 out·1M·99.9% up
  • Z.aifp8$1.40 in·$4.40 out·1M·100% up
Polaris 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 5.2 and Polaris Alpha?

GLM 5.2 is developed by Zhipu AI while Polaris Alpha is developed by OpenRouter. GLM 5.2 has a 1.0M token context window vs Polaris Alpha's 256K. You can compare their actual outputs across 34 challenges on Rival to see how they differ in practice.

Which is better, GLM 5.2 or Polaris Alpha?

It depends on your use case. GLM 5.2 and Polaris Alpha each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 34 challenges so you can judge which fits your needs best.

How much does GLM 5.2 cost compared to Polaris Alpha?

GLM 5.2 costs $1.4/M input tokens and Polaris Alpha costs $0/M input tokens. Polaris Alpha is $1.40/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 5.2 and Polaris Alpha on Rival?

This page shows a side-by-side comparison of GLM 5.2 and Polaris 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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  • Polaris Alpha vs Mistral Large 4Landed Oct 2026
  • GLM 5.2 vs GPT-6.1 SolLanded Sep 2026
  • Polaris Alpha vs Claude Sonnet 5.5Landed Sep 2026
  • GLM 5.2 vs Solar Mini 4Landed Sep 2026
  • Polaris Alpha vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

  • GLM 5.2 vs GLM 5.3Same lab
  • GLM 5.2 vs GLM 5.3 FlashSame lab
  • Polaris Alpha vs Ox AlphaSame lab
  • Polaris Alpha vs OpenRouter Fusion · Budget (Jun 2026)Same lab
  • GLM 5.2 vs Llama 3 70BNew provider
  • GLM 5.2 vs Llama 3.1 405BSame size
  • GLM 5.2 vs Llama 3.1 70B (Instruct)New provider
  • GLM 5.2 vs Llama 4 MaverickSame size

Model pages

  • GLM 5.258 outputs, specs and price
  • Polaris Alpha35 outputs, specs and price
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