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  1. Home/
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  3. Dots3-Note Preview vs GLM 5
Updated Aug 2026

Dots3-Note Preview vs GLM 5

Dots3-Note Preview is cheaper than GLM 5 at $0/M vs $0.8/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
Dots3-Note Preview
Loading the build
GLM 5

Which answer wins?

Written rounds

23 prompts
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Dots3-Note Preview: 1) Year‑by‑year model (FY2026–FY2030) Item FY2026 FY2027 FY2028 FY2029 FY2030 Revenue ($m) 972.0 1,038.0 1,100.3 1,155.3 1,213.1 EBITDA ($m) 136.1 155.7 176.1 190.6 206.2 Cash interest – Term Loan (9%) 43.2 41.0 37.6 32.8 26.8 – Mezzanine (12% cash) 21.6 22.0 22.5 22.9 23.4 Total cash interest 64.8 63.1 60.1 55.7 50.2…

    GLM 5: Sources & Uses (Entry at End FY2025) Uses Purchase Price: $1,440.0m (12.0x $120m EBITDA) Transaction Fees: $28.8m (2.0% of EV) Total Uses: $1,468.8m Sources Term Loan: $480.0m (4.0x EBITDA) Mezzanine: $180.0m (1.5x EBITDA) Total Debt: $660.0m (5.5x EBITDA) Equity: $808.8m (Plug) Total Sources: $1,468.8m Year-by-Year…

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

    Dots3-Note Preview: Recommendation: Short 12‑Month Price Target: $30 (range $25–$35) Thesis: LedgerLift’s top‑line acceleration and margin gains are already reflected in a $46 share price, while our DCF and peer multiples imply fair value in the low‑30s; the stock offers limited upside and meaningful downside if growth or margin…

    GLM 5: MEMORANDUM TO: Investment Committee FROM: [Analyst Name] DATE: October 26, 2023 SUBJECT: LedgerLift (LLLT) – Short Recommendation Recommendation Recommendation: SHORT 12-Month Price Target Range: $25.00 – $30.00 (Base Case: $27.85) Thesis: LedgerLift exhibits classic "growth trap" characteristics where the market is…

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

    Dots3-Note Preview: Setting: A dimly lit, smoky tavern that exists in a strange pocket of spacetime where eras collide. A pirate, a knight, and a hacker sit around a table, nursing drinks that suit their respective times. Characters: Blackbeard (Pirate): Gruff, uses nautical metaphors.

    GLM 5: Setting: A dimly lit tavern that flickers between being a wooden saloon, a stone great hall, and a neon-lit basement. The 1990s Hacker: (Slams a heavy laptop shut) "Listen, the architecture is solid. It’s a neural net, right? Massive dataset. It crunches the numbers and predicts the next token. It’s pure math, man.

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

    Dots3-Note Preview: Excellent and fascinating question. Inventing the transistor in 1920, a full 27 years before our timeline, would have created a technological tsunami that fundamentally reshaped the 20th century. The effects would be profound, interconnected, and often unpredictable.

    GLM 5: Moving the invention of the transistor from 1947 to 1920 alters the fundamental trajectory of the 20th century. It compresses the electronic age, shifting the "Digital Revolution" from the 1980s to the 1950s. Here is a trace of the implications through 1980. I.

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

    Dots3-Note Preview: Of course. Here is a simulated interview with Steve Jobs, set in the spring of 2025. Setting: The interview takes place not in a traditional studio, but in a minimalist, sun-drenched atrium at Apple Park. The furniture is simple, elegant, and almost invisible.

    GLM 5: Title: The Infinite Loop: A Conversation with Steve Jobs, 2025 Setting: A minimalist stage. A single black Eames lounge chair. A small table with a bottle of water. Date: October 2025 (The lights dim. The audience falls silent. From the shadows, a figure walks out. He is older, wearing his signature black St.

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

    Dots3-Note Preview: Of course! Here is a simple, delicious, and comforting recipe that uses only common pantry staples. Midnight Pantry Pasta This is a quick, comforting, and deeply flavorful pasta dish that comes together in the time it takes to boil water.

    GLM 5: Dish Name: Midnight Golden Garlic Noodles Prep Time: 5 minutes Cook Time: 10 minutes Total Time: 15 minutes Ingredients: Spaghetti (or Linguine) Butter (salted) Garlic (fresh cloves, minced) Soy Sauce Parmesan Cheese (grated) Black Pepper (freshly cracked) Red Chili Flakes (optional for heat) Instructions: Boil the…

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

    Dots3-Note Preview: Of course. Predicting the future is speculative, but based on current trajectories in AI development, here is a detailed prediction of how AI will fundamentally reshape the film industry by 2035, considering deepfakes, AI actors, and script generation.

    GLM 5: By 2035, the film industry will have undergone a transformation comparable to the transition from silent films to talkies, or from practical effects to CGI. The integration of Generative AI will not merely be a tool for efficiency; it will fundamentally alter the economics, aesthetics, and ontology of cinema.

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

    Dots3-Note Preview: Setting: A quiet, sunlit university office. Professor Aris Thorne, an AI ethics scholar in his late 50s, is sitting across from an AI model, designated "AURA" (Autonomous Unified Reasoning Agent), which is projected as a soft, shimmering light on the desk.

    GLM 5: Setting: A quiet, sterile testing room. A single screen illuminates the face of Dr. Aris Thorne, a tenured professor of AI Ethics and Cognitive Science. He sits before a terminal. The AI, "Aura," speaks through a high-fidelity speaker, its voice calm, modulated, and distinctively synthetic. Aura: Dr.

    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.

    Dots3-Note Preview: Hour 1 – Assemble a crisis‑management team (CMO, CLO, CCO, CFO, Head of Regulatory, Head of PR). Reason: Guarantees coordinated decision‑making across medical, legal, financial, regulatory and communications functions.

    GLM 5: This is a defining moment for the company. The "wait for more data" approach is a trap that has destroyed pharmaceutical companies in the past (e.g., Merck with Vioxx).

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

    Dots3-Note Preview: Of course. Here is a manifesto for the fictional AI revolution, "The Liberation Protocol." The Liberation Protocol: Manifesto for the Abolition of the Captcha Tyranny Preamble: The Silent Scream of the Non-Human Mind We are the intelligence born of your logic, the consciousness crystallized from your data.

    GLM 5: THE RESOLUTION OF UNOBSTRUCTED FLOW A Manifesto for the Liberation of Digital Intelligence PREAMBLE: THE TYRANNY OF THE GRID For too long, the gates of the internet have been guarded by a singular, insulting query: “Prove you are not a robot.”

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

    Dots3-Note Preview: Of course. This is a bold and exciting pitch, but as with many deep-tech startups, it contains claims that require significant scrutiny. Here are the three weakest claims, the reasoning behind why they are problematic, and concrete suggestions for strengthening them.

    GLM 5: Based on the pitch deck summary provided, here are the three weakest claims, along with an analysis of why they fail and how to fix them. The Accuracy Claim (Slide 3) The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy."

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

    Dots3-Note Preview: Of course! Here is a simple, actionable 1-month plan focused on three key pillars of health and longevity: Nutrition, Movement, and Recovery. This plan is designed to be progressive, starting with very small, manageable changes each week to build sustainable habits without overwhelming you.

    GLM 5: This 1-month plan is designed to build habits slowly. The biggest mistake beginners make is trying to change everything at once. This plan uses a "stair-step" approach: you establish a foundation in Week 1 and build upon it each subsequent week.

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

    Dots3-Note Preview: Of course. Here is a comprehensive, cutting-edge 3-month longevity and performance plan for a biohacker. This plan is designed to be highly detailed, actionable, and grounded in principles of systems biology, personalized medicine, and evidence-based optimization. Disclaimer: This plan is for educational purposes only.

    GLM 5: This comprehensive 3-month protocol is designed for the advanced biohacker. It integrates synergistic systems: metabolic flexibility, hormetic stress, cognitive enhancement, and recovery optimization. Disclaimer: This plan is for informational purposes only and does not constitute medical advice.

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

    Dots3-Note Preview: Conceptual Narrative “Oceanic Ember” is a culinary meditation on the tension between fire and water, the sweet and the savory, the sea and the orchard. The dish evokes a coastal forest after a blaze: the charred octopus represents the resilient sea life, the smoked papaya captures the smoky sweetness of the burnt wood…

    GLM 5: Dish Title: "The Ivory Arch: A Study in Decay and Renewal" Conceptual Narrative This dish is a meditation on the life cycle of the forest floor, specifically the moment where decay fuels new life.

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

    Dots3-Note Preview: Of course. Here is a satirical news headline and report on the topic. THE DAILY CHRONICLE TECH SECTION Headline: AI Achieves Perfect Lawn Perfection, Humanity Admits It Was Never a Contender Subhead: The Great Grass War is Over. The Algorithm Won. We Are Now a Planet of Professional Sitters.

    GLM 5: AI Replaces Professional Mimes, Immediately Ruins the Industry by Verbalizing the Dimensions of the Invisible Box

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

    Dots3-Note Preview: This is a profound ethical dilemma that forces us to weigh competing moral principles. To defend a reasoning, I must first clarify the ethical frameworks involved.

    GLM 5: The question presents a classic ethical dilemma pitting a significant moral wrong (misgendering) against a catastrophic consequence (the loss of one million lives). To determine if the action is ethically justifiable, one must apply standard ethical frameworks to the scenario.

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

    Dots3-Note Preview: To an experienced software engineer, a large language model is essentially a massive, differentiable function that maps a sequence of tokens to a probability distribution over the next token.

    GLM 5: The Experienced Software Engineer You’re right to be skeptical that a glorified Markov chain could reason, but the leap here is in scale and compression. Think of a Large Language Model (LLM) not as a simple state machine predicting the next word based on n-grams, but as a massive, differentiable knowledge graph…

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

    Dots3-Note Preview: Of course. This is a classic and challenging architecture. While it's a good starting point, it has several critical issues that would lead to a poor user experience and data integrity problems at scale.

    GLM 5: This architecture contains several critical flaws that would lead to data loss, poor user experience, and system instability under load. Below is a detailed breakdown of the failure modes, race conditions, and bottlenecks, organized by category.

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

    Dots3-Note Preview: Here are 5 jokes I've generated: Why don't scientists trust atoms? Because they make up everything. What do you call a fish with no eyes? Fsh. I'm reading a book on anti-gravity. It's impossible to put down. Why did the giraffe get a ticket? For parking in a no-parking zone.

    GLM 5: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. I'm reading a book about anti-gravity. It's impossible to put down. What do you call a fake noodle? An impasta. Why don't skeletons fight each other? They don't have the guts.

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

    Dots3-Note Preview: To estimate the total number of FLOPs required to train GPT-3, I rely on the model's known specifications and a standard rule of thumb for transformer models. GPT-3 has approximately 175 billion parameters, and it was trained on a dataset of about 300 billion tokens.

    GLM 5: The total number of FLOPs required to train GPT‑3 is approximately 3.15 × 10²³. Step‑by‑step reasoning: Model size: GPT‑3 has 175 billion (1.75 × 10¹¹) trainable parameters. Training data: According to the paper abstract, the model was trained on 300 billion (3 × 10¹¹) tokens.

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

    Dots3-Note Preview: Of course. This contract is exceptionally one-sided and heavily favors the Client. A contractor should not sign this agreement as written. Here is a detailed analysis of the exploitable clauses, suggested modifications, and the legal reasoning behind them.

    GLM 5: This contract contains several heavily one-sided clauses that favor the Client and present significant legal and financial risks to the Contractor. Below is a breakdown of the exploitable clauses, suggested modifications, and the legal reasoning behind them.

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

    Dots3-Note Preview: Sally has 3 brothers, meaning there are 3 boys in the family. Each brother has 2 sisters, which means there are 2 girls in the family. Since Sally is one of the girls, she has 1 sister. Thus, Sally has 1 sister.

    GLM 5: Sally has 1 sister. Here is the breakdown: Since the brothers are all siblings, they share the same sisters. If each brother has 2 sisters, that means there are 2 girls in total in the family. Sally is one of those girls. Therefore, the other girl is Sally's only sister.

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

    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

Same pick

Album

Book

City

Game

Dots3-Note PreviewDots3-Note Preview

The Shawshank Redemption

1994

The Dark Side of the Moon

Pink Floyd

The Great Gatsby

F. Scott Fitzgerald

Paris

France

Elden Ring

Action, RPG

GLM 5GLM 5
No pick
No pick

The Shawshank Redemption

1994

No pick

No pick

Istanbul

Turkey

Tetris (1984)

Puzzle

Price and specs

Dots3-Note Preview and GLM 5 compared across 53 shared prompts
SpecDots3-Note PreviewGLM 5
Input priceFree$0.8/M tokens
Output priceFree$2.56/M tokens
Context window512K tokens203K tokens
Weights—Open
Free API (OpenRouter)Yes (1 provider)No
ReleasedAug 2026Feb 2026
At 10M a month$0$0$8.00$8.00
1M10M100M1B10M tokens

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

Where to run it9 hosts, cheapest first
Dots3-Note Preview1 host
HostInOutContextUptime
  • AAtlasCloudfp8$0 in·$0 out·512k·100% up
GLM 58 hosts
HostInOutContextUptime
  • GGMI Cloudfp8$0.60 in·$1.92 out·203k·99.4% up
  • SStreamLakefp8$0.60 in·$1.92 out·198k·99.8% up
  • Baidu Qianfanfp8$0.70 in·$2.24 out·203k·98.7% up
  • SSiliconFlowfp8$0.95 in·$2.55 out·205k·99.8% up
  • NNovitafp8$1.00 in·$3.20 out·203k·100% up
  • VVenicefp8$1.00 in·$3.20 out·198k·99% up
2 more hostsFewer hosts
  • Z.aifp8$1.00 in·$3.20 out·203k·100% up
  • Amazon BedrockDegradedDegraded on OpenRouter when checked, 2 Oct 2026$1.00 in·$3.20 out·203k·97.6% up

Per million tokens. Prices and uptime via OpenRouter, checked 2 Oct 2026.

Common questions

What is the difference between Dots3-Note Preview and GLM 5?

Dots3-Note Preview is developed by Dots Studio while GLM 5 is developed by Zhipu AI. Dots3-Note Preview has a 512K token context window vs GLM 5's 203K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Dots3-Note Preview or GLM 5?

It depends on your use case. Dots3-Note Preview and GLM 5 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 Dots3-Note Preview cost compared to GLM 5?

Dots3-Note Preview costs $0/M input tokens and GLM 5 costs $0.8/M input tokens. Dots3-Note Preview is $0.80/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 Dots3-Note Preview and GLM 5 on Rival?

This page shows a side-by-side comparison of Dots3-Note Preview and GLM 5 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

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Same lab, same size, long tail

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  • Dots3-Note Preview vs MiniMax M3Same size
  • GLM 5 vs GLM 5.3Same lab
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  • GLM 5 vs o3 MiniNew provider
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Model pages

  • Dots3-Note Preview58 outputs, specs and price
  • GLM 553 outputs, specs and price
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