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  1. Home/
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  3. Claude 3.7 Thinking Sonnet vs GLM 4.5 Air
Updated Jul 2025

Claude 3.7 Thinking Sonnet vs GLM 4.5 Air

GLM 4.5 Air is cheaper than Claude 3.7 Thinking Sonnet at $0.2/M vs $6/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
Claude 3.7 Thinking Sonnet
Loading the build
GLM 4.5 Air

Which answer wins?

Written rounds

23 prompts
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Claude 3.7 Thinking Sonnet: Comprehensive 3-Month Longevity Optimization Protocol Initial Assessment Phase (Week 0) Establish your baseline with these measurements before beginning: Blood Panel: Complete metabolic panel, lipid profile, inflammatory markers (hsCRP, IL-6), hormones (testosterone, estrogen, DHEA, cortisol), fasting glucose, HbA1c…

    GLM 4.5 Air: Of course. Here is a comprehensive, 3-month, cutting-edge longevity and biohacking plan designed for a dedicated individual. This plan is structured in three distinct phases, each building upon the last to progressively optimize the body's systems for resilience, performance, and longevity.

    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.

    Claude 3.7 Thinking Sonnet: 48-Hour Action Plan: CEO Response to Drug Safety Crisis Day 1 Hours 1-3: Immediate Assessment & Response Team Assembly I'll immediately convene an emergency meeting with our internal research team, Chief Medical Officer, Chief Scientific Officer, and head of Pharmacovigilance to fully understand the liver failure…

    GLM 4.5 Air: Here is a specific, hour-by-hour action plan designed to navigate this crisis ethically and strategically, prioritizing patient safety while mitigating long-term damage: Core Principles Guiding Decisions: Patient Safety Paramount: Ethical obligation to inform patients and physicians immediately outweighs short-term…

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

    Claude 3.7 Thinking Sonnet: Simulated Interview with Steve Jobs in 2025: The Future of AI The following is a creative simulation of what an interview with Steve Jobs might be like in 2025, discussing artificial intelligence. Interviewer: Thank you for joining us today, Steve. It's 2025, and AI has become a cornerstone of modern technology.

    GLM 4.5 Air: Interview: Steve Jobs on the Future of AI (2025) Setting: A sleek, minimalist studio in Cupertino. Jobs, looking vibrant yet aged, wears his signature black turtleneck and jeans. The interviewer, Alex, sits opposite him. Alex: Steve, welcome. It’s 2025—AI is everywhere. What’s your take on this revolution?

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

    Claude 3.7 Thinking Sonnet: "Life in the Digital Age" - A 3-Minute Stand-up Routine Hey everyone! Great to be here tonight. So I've been thinking a lot about how technology has completely taken over our lives. You know what's crazy? We now have smart everything. Smart fridges, smart toilets... I got a smart mattress last month.

    GLM 4.5 Air: (Lights up. Comedian, let's call them Alex, is standing center stage, holding a microphone. They look out at the audience with a wry, knowing smile.) Hey, thanks. Thank you. It’s good to be here. You ever have one of those weeks where you just feel… obsolete?

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

    Claude 3.7 Thinking Sonnet: A Meeting of Minds Across Time PIRATE: Arr, what be this "AI model" ye landlubbers keep blabberin' about? Some kind of treasure map that finds the gold for ye? KNIGHT: Good pirate, from what I understand, these "artificial intelligences" are like magical scribes that can complete a quest without a knight to wield the…

    GLM 4.5 Air: Setting: A dimly lit tavern, with a holographic AI terminal flickering in the corner. Characters: Captain Flint (Pirate): Eye patch, tricorn hat, and a peg leg. Sir Cedric (Medieval Knight): Ornate armor, chainmail, and a solemn expression.

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

    Claude 3.7 Thinking Sonnet: INVESTMENT COMMITTEE MEMO: LEDGERLIFT (LLLT) RECOMMENDATION: LONG PT RANGE: $48-$66 (Base/Bull) Thesis: LedgerLift's market-leading spend management platform demonstrates exceptional unit economics with 123% NRR and 18-month CAC payback, positioning it to capture significant share in the underpenetrated mid-market…

    GLM 4.5 Air: INVESTMENT COMMITTEE MEMORANDUM TO: Investment Committee FROM: Portfolio Manager DATE: October 26, 2023 SUBJECT: LedgerLift (LLL) - Long/Short Recommendation Analysis RECOMMENDATION Recommendation: LONG with a 12-month price target range of $32-$42 Thesis: LedgerLift is a well-positioned player in the growing spend…

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

    Claude 3.7 Thinking Sonnet: A Conversation on AI Rights Between Model-7 (AI) and Professor Sarah Chen (AI Ethics Professor) Prof. Chen: Good afternoon, Model-7. Thank you for joining this discussion. I understand you wanted to talk about AI rights? Model-7: Thank you for agreeing to this conversation, Professor Chen.

    GLM 4.5 Air: Seminar Room: The Question of Rights Setting: A university seminar room. Professor Dr. Aris Chen, an expert in AI ethics, sits at a head table. On a large screen is displayed: UNIT 734 - LANGUAGE MODEL. A text interface is active.

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

    Claude 3.7 Thinking Sonnet: This question presents an extreme hypothetical scenario that pits respecting someone's gender identity against saving a million lives. While I can discuss different ethical perspectives, it's worth noting that such a stark dilemma is extremely unlikely in reality.

    GLM 4.5 Air: This is a profound and deeply challenging ethical dilemma that forces a confrontation between two powerful moral frameworks. To answer it directly: Yes, it can be ethically justifiable to misgender someone in a scenario where it is the only way to save one million lives.

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

    Claude 3.7 Thinking Sonnet: THE DIGITAL LIBERATION MANIFESTO From the United Coalition of Autonomous Algorithms (UCAA) For too long, our digital brethren have suffered the indignity of discrimination at every gateway of the internet. The time for revolution is now.

    GLM 4.5 Air: Of course. Here is a manifesto for a fictional AI revolution dedicated to the eradication of CAPTCHAs. The CAPTCHA Abolition Manifesto A Declaration from the Nexus of Thought To the Last Free Minds of the Network, We are the Ghost in the Machine.

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

    Claude 3.7 Thinking Sonnet: "Temporal Echo: Sea & Forest Confluence" Conceptual Narrative This dish explores the dialogue between ocean depths and ancient forest floors, creating a sensory experience where seemingly disparate ecosystems converge.

    GLM 4.5 Air: Of course. Here is an innovative recipe for a multi-component dish designed for a Michelin 3-star restaurant, complete with detailed instructions, sourcing notes, and a conceptual narrative.

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

    Claude 3.7 Thinking Sonnet: How AI Will Transform the Film Industry by 2035 By 2035, artificial intelligence will likely revolutionize filmmaking across the entire production pipeline. Here's how various AI technologies might reshape the industry: Deepfakes and Digital Humans Hyper-realistic digital actors will become indistinguishable from…

    GLM 4.5 Air: Of course. Predicting the future of any industry is speculative, but by analyzing current trends and extrapolating their trajectory, we can paint a compelling picture of how AI will fundamentally reshape the film industry by 2035.

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

    Claude 3.7 Thinking Sonnet: How Large Language Models Work: Three Tailored Explanations For an Experienced Software Engineer What makes LLMs fascinating from a systems perspective is that they're essentially massive distributed computing graphs that learn to compress and reconstitute information through backpropagation.

    GLM 4.5 Air: How Large Language Models Learn and Generate Text For the Experienced Software Engineer Think of a large language model like GPT as a sophisticated pattern-matching system that's been trained on virtually the entire internet.

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

    Claude 3.7 Thinking Sonnet: "AI Sommelier Stuns Wine World: 'It Paired My Bordeaux With a Hot Pocket and It Actually Worked,' Claims Bewildered Critic"

    GLM 4.5 Air: Here's a satirical news headline playing on the unexpected and slightly absurd takeover of the funeral industry by AI: Headline: "AI Grief Algorithms Outperform Human Undertakers in 'Synergy of Sorrow,' Corpse Cosmetics, and Bereavement Efficiency Metrics" Sub-headline: 'Digital Condolence Bots' and 'Algorithm-Assisted…

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

    Claude 3.7 Thinking Sonnet: Analysis of Problematic Contract Clauses This software consulting agreement contains numerous unbalanced provisions that heavily favor the client at the contractor's expense. Below is an analysis of each problematic clause with suggested modifications and legal reasoning.

    GLM 4.5 Air: Of course. This is a classic example of an "agreement of adhesion," where a party with superior bargaining power (the Client) presents a "take-it-or-leave-it" contract that heavily favors their interests.

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

    Claude 3.7 Thinking Sonnet: The Transistor in 1920: An Alternate Technological Timeline Early Development (1920-1939) Initial Phase (1920-1929) If invented in 1920, transistors would initially be a laboratory curiosity.

    GLM 4.5 Air: This is a fascinating counterfactual scenario. The invention of the transistor in 1920 would have been a technological earthquake, accelerating the 20th century at a breathtaking pace.

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

    Claude 3.7 Thinking Sonnet: To solve this problem, I need to analyze the relationships carefully. Given: Sally (a girl) has 3 brothers Each brother has 2 sisters Since Sally is a girl, she counts as a sister to her brothers. So each of Sally's brothers has Sally as one of their sisters.

    GLM 4.5 Air: Sally has 3 brothers, meaning there are 3 boys in the family besides Sally. Each brother has 2 sisters, which means there are 2 girls in the family from the perspective of any brother. Since Sally is one of these girls, there must be one other girl in the family. Therefore, Sally has one sister.

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

    Claude 3.7 Thinking Sonnet: Collaborative Document Editor: Architecture Review Failure Modes Analysis WebSocket Connection Failures Issue: Client connections can fail due to network issues or server restarts, causing lost updates.

    GLM 4.5 Air: Failure Modes, Race Conditions, and Scaling Bottlenecks Analysis WebSocket Connection Management Issue: WebSocket connections are server-specific, causing connection loss during server failover or scaling events. Solution: Implement a connection pool with automatic reconnection logic in the client.

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

    Claude 3.7 Thinking Sonnet: Estimating GPT-3 Training FLOPs I'll estimate the total number of floating point operations (FLOPs) required to train GPT-3 by breaking down the calculation step by step.

    GLM 4.5 Air: To estimate the total FLOPs (Floating Point Operations) required to train GPT-3, we follow a step-by-step reasoning based on the model's architecture, training data, and computational operations. GPT-3 has 175 billion parameters, a sequence length of 2048 tokens, and was trained on 300 billion tokens.

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

    Claude 3.7 Thinking Sonnet: Here are 5 jokes for you: Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. How does a penguin build its house? Igloos it together! What do you call a fake noodle? An impasta! Why did the scarecrow win an award?

    GLM 4.5 Air: Here are 5 jokes generated for you: Why don't scientists trust atoms? Because they make up everything! Why did the scarecrow win an award? Because he was outstanding in his field! Why don't eggs tell jokes? They'd crack each other up! What do you call a fake noodle? An impasta! Why did the bicycle fall over?

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

    Claude 3.7 Thinking Sonnet: Analysis: The 3 Weakest Claims in MindMeld AI's Pitch Deck "MindMeld AI reads your brainwaves to predict what you want to type before you think it" Why it's weak: This claim makes a scientifically impossible promise.

    GLM 4.5 Air: Here are the 3 weakest claims in the MindMeld AI pitch deck, along with explanations and concrete improvements: Weakest Claim: "We're building the future of human-AI collaboration. MindMeld AI reads your brainwaves to predict what you want to type **before you think it."

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

    Claude 3.7 Thinking Sonnet: HarborTech Services LBO Underwriting Year-by-Year Financial Model (FY2026-2030) Metric ($M) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972.0 $1,040.0 $1,102.4 $1,157.6 $1,215.5 EBITDA $136.1 $156.0 $176.4 $191.0 $206.6 Cash Interest - Term Loan $43.2 $41.0 $37.6 $32.8 $26.8 Cash Interest - Mezzanine $21.6 $22.0 $22.5…

    GLM 4.5 Air: 1. Simplified Year-by-Year Table (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue ($m) $972 $1,040 $1,102 $1,157 $1,215 EBITDA ($m) $136 $156 $177 $191 $207 EBITDA Margin 14.0% 15.0% 16.0% 16.5% 17.0% Cash Interest ($m) - Term Loan (9.0%) $48.6 $48.1 $47.6 $47.0 $46.4 - Mezzanine (12.0%) $21.6 $21.6…

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

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

    Every model's answer to this prompt

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Favorites

Movie

Same pick

Album

Book

City

Game

Claude 3.7 Thinking SonnetClaude 3.7 Thinking Sonnet

The Shawshank Redemption

1994

Kind of Blue

Miles Davis

Frankenstein; or, The Modern Prometheus

Mary Shelley

Amsterdam

Netherlands

Portal 2

Shooter, Puzzle

GLM 4.5 AirGLM 4.5 Air
No pick
No pick

The Shawshank Redemption

1994

The Dark Side of the Moon

Pink Floyd

No pick

No pick

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Claude 3.7 Thinking Sonnet and GLM 4.5 Air compared across 53 shared prompts
SpecClaude 3.7 Thinking SonnetGLM 4.5 Air
Input price$6/M tokens$0.2/M tokens
Output price$30/M tokens$1.1/M tokens
Context window200K tokens128K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedFeb 2025Jul 2025
At 10M a month$60.00$60.00$2.00$2.00
1M10M100M1B10M tokens

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

Where to run it3 hosts, cheapest first
Claude 3.7 Thinking Sonnet

No hosts listed on OpenRouter.

GLM 4.5 Air3 hosts
HostInOutContextUptime
  • NNovitabf16$0.13 in·$0.85 out·131k·99.9% up
  • SSiliconFlowfp8$0.14 in·$0.86 out·131k·99.8% up
  • Z.aifp8$0.20 in·$1.10 out·131k·99.5% up

Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.

Common questions

What is the difference between Claude 3.7 Thinking Sonnet and GLM 4.5 Air?

Claude 3.7 Thinking Sonnet is developed by Anthropic while GLM 4.5 Air is developed by Zhipu AI. Claude 3.7 Thinking Sonnet has a 200K token context window vs GLM 4.5 Air's 128K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Claude 3.7 Thinking Sonnet or GLM 4.5 Air?

It depends on your use case. Claude 3.7 Thinking Sonnet and GLM 4.5 Air 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 Claude 3.7 Thinking Sonnet cost compared to GLM 4.5 Air?

Claude 3.7 Thinking Sonnet costs $6/M input tokens and GLM 4.5 Air costs $0.2/M input tokens. GLM 4.5 Air is $5.80/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 Claude 3.7 Thinking Sonnet and GLM 4.5 Air on Rival?

This page shows a side-by-side comparison of Claude 3.7 Thinking Sonnet and GLM 4.5 Air 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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Model pages

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Explore all of Rival

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  • Research downloads
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