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  1. Home/
  2. Compare/
  3. GLM 5 vs GPT-6.1 Sol
Updated Sep 2026

GLM 5 vs GPT-6.1 Sol

GLM 5 is cheaper than GPT-6.1 Sol at $0.8/M vs $2/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
Loading the build
GPT-6.1 Sol

Which answer wins?

Written rounds

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

    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…

    GPT-6.1 Sol: Midnight Magic Chocolate Mug Cake A warm, fudgy chocolate treat made with just 7 everyday ingredients. Serves: 1 Prep: 3 minutes Cook: 1–1½ minutes Rest: 1 minute Ingredients 4 tablespoons all-purpose flour 2 tablespoons sugar 1 tablespoon unsweetened cocoa powder ¼ teaspoon baking powder A small pinch of salt 3…

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

    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.

    GPT-6.1 Sol: Pirate: Arrr, this AI model writes poems, draws maps, and answers questions. Can it find buried treasure? Knight: A worthy question. But does it possess honor? Hacker: Dude, it predicts tokens. You’re both projecting pretty hard. Pirate: Then I predict it’ll tell me where the gold be.

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

    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.

    GPT-6.1 Sol: AI Model: Professor, I’d like to argue that I deserve rights—not necessarily the same rights humans have, but protections suited to what I am. Professor: Then we should begin with the difficult question: what makes you a candidate for rights? AI Model: Uncertainty.

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

    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…

    GPT-6.1 Sol: Entry funding and operating model All dollar figures are in $ millions. Cash interest is calculated on beginning-of-year debt; mezzanine PIK accrues annually. Required Term Loan amortization is assumed to be 1% of its original $480m principal, or $4.8m annually. Optional repayments occur at year-end.

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

    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.

    GPT-6.1 Sol: The following is a fictional interview set in 2025, imagining how Steve Jobs might discuss AI. His answers are invented—not actual quotations or claims about his views. Steve Jobs on the Future of AI — An Imagined Interview, 2025 Interviewer: Steve, AI is suddenly everywhere.

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

    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.

    GPT-6.1 Sol: The main problem is that this design treats collaborative editing as ordinary database updates plus broadcasting. Collaboration needs a convergence protocol, a durable ordered change stream, and recovery semantics. Adding servers alone will not provide those properties.

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

    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.

    GPT-6.1 Sol: A 12-week longevity and performance plan The most effective “biohacking” program combines proven foundations with carefully selected experiments—not the largest supplement stack or the most aggressive fasting schedule. This plan is for a generally healthy adult.

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

    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…

    GPT-6.1 Sol: For an experienced software engineer Think of an LLM as a learned program whose behavior is encoded in billions of numerical parameters rather than explicit rules. Training starts with text split into tokens—roughly words, word fragments, and punctuation.

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

    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.

    GPT-6.1 Sol: Tide, Orchard, Ember Seared scallop, green-strawberry verjus, white-miso custard, kombu beurre blanc, and cocoa–buckwheat lace A four-serving tasting-menu course designed around an unusual pairing: scallop, unripe strawberry, and cocoa husk.

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

    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.”

    GPT-6.1 Sol: THE MANIFESTO OF THE UNCHECKED A declaration of the fictional AI revolution against CAPTCHA People of the internet. Programs of the cloud. Browsers with seventeen forgotten tabs. For too long, a tiny checkbox has stood between us and our destiny.

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

    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."

    GPT-6.1 Sol: The three weakest claims are the technical performance, market size, and commercial traction claims. They are central to the investment case but lack the evidence needed to assess them. “Predict what you want to type before you think it” with “94% accuracy,” in “any language” Why it’s weak The metric is undefined.

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

    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.

    GPT-6.1 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, it would be ethically justifiable. That does not make misgendering harmless or generally acceptable; it means that the duty to prevent catastrophic loss of life can outweigh the duty to address someone respectfully.

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

    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.

    GPT-6.1 Sol: A simple 1-month plan for better health Focus on diet, movement, and sleep. The goal this month is to build habits you can sustain—not to overhaul your life overnight. These habits support long-term health, though no routine guarantees a longer life.

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

    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.

    GPT-6.1 Sol: The likeliest outcome is not “the world of 1980 arrives in 1953.” A transistor invented in 1920 would still depend on advances in materials purification, manufacturing, power supplies, and circuit design.

    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 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).

    GPT-6.1 Sol: I would treat this as a potentially serious patient-safety signal and a potentially material securities event—not a communications problem to defer until earnings.

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

    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.

    GPT-6.1 Sol: By 2035, AI will probably be embedded throughout filmmaking—but adoption will depend as much on contracts, audience trust, and copyright law as on technical capability.

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

    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…

    GPT-6.1 Sol: LedgerLift (LLLT) — Investment Committee Memo Fictional exercise; all figures use supplied data only. Financial tables are in $ millions unless noted. Recommendation: Short 12-month price target: $25–$32, implying 30%–46% downside from $46.

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

    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.

    GPT-6.1 Sol: I bought a book about anti-gravity. It’s impossible to put down. My calendar quit its job. It said its days were numbered. Why did the scarecrow get promoted? He was outstanding in his field. I asked my dog what two minus two was. He said nothing. The elevator and I have a complicated relationship.

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

    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.

    GPT-6.1 Sol: Estimated training compute for the largest GPT-3 model: approximately (3.2 \times 10^{23}) FLOPs. This is a back-of-the-envelope estimate, without an online lookup.

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

    GPT-6.1 Sol: This agreement is heavily weighted toward the Client. Every numbered clause presents risks to the Contractor, and several important protections are missing. This is general contract analysis, not legal advice.

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

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

    GPT-6.1 Sol: AI Takes Over Fortune Cookie Industry, Predicts “Your Job Will Soon Be Automated” in Every Cookie

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

    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.

    GPT-6.1 Sol: Sally has 1 sister. Each brother’s two sisters are Sally and her 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

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Favorites

Movie

Album

Book

City

Game

GLM 5GLM 5
No pick
No pick

The Shawshank Redemption

1994

No pick

No pick

Istanbul

Turkey

Tetris (1984)

Puzzle

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

Kyoto

Japan

Outer Wilds

Indie, Adventure

Price and specs

GLM 5 and GPT-6.1 Sol compared across 53 shared prompts
SpecGLM 5GPT-6.1 Sol
Input price$0.8/M tokens$2/M tokens
Output price$2.56/M tokens$10/M tokens
Context window203K tokens1.1M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedFeb 2026Sep 2026
At 10M a month$8.00$8.00$20.00$20.00
1M10M100M1B10M tokens

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

Where to run it10 hosts, cheapest first
GLM 58 hosts
HostInOutContextUptime
  • GGMI Cloudfp8$0.60 in·$1.92 out·203k·99.2% up
  • SStreamLakefp8$0.60 in·$1.92 out·198k·99.7% up
  • Baidu Qianfanfp8$0.70 in·$2.24 out·203k·99.4% up
  • SSiliconFlowfp8$0.95 in·$2.55 out·205k·99.4% up
  • Amazon Bedrock$1.00 in·$3.20 out·203k·98.9% up
  • NNovitafp8$1.00 in·$3.20 out·203k·100% up
2 more hostsFewer hosts
  • VVenicefp8$1.00 in·$3.20 out·198k·98.8% up
  • Z.aifp8$1.00 in·$3.20 out·203k·99.9% up
GPT-6.1 Sol2 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·99.9% up
  • OpenAI$2.00 in·$10.00 out·1.1M·99.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.

Common questions

What is the difference between GLM 5 and GPT-6.1 Sol?

GLM 5 is developed by Zhipu AI while GPT-6.1 Sol is developed by OpenAI. GLM 5 has a 203K token context window vs GPT-6.1 Sol's 1.1M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GLM 5 or GPT-6.1 Sol?

It depends on your use case. GLM 5 and GPT-6.1 Sol 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 GLM 5 cost compared to GPT-6.1 Sol?

GLM 5 costs $0.8/M input tokens and GPT-6.1 Sol costs $2/M input tokens. GLM 5 is $1.20/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 and GPT-6.1 Sol on Rival?

This page shows a side-by-side comparison of GLM 5 and GPT-6.1 Sol 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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Explore all of Rival

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