Skip to content
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed
  1. Home/
  2. Compare/
  3. GLM 4.6 vs GPT-6.1 Sol
Updated Sep 2026

GLM 4.6 vs GPT-6.1 Sol

GLM 4.6 is cheaper than GPT-6.1 Sol at $0.4/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 4.6
Loading the build
GPT-6.1 Sol

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.

    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 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.

    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 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.

    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 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…

    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
  • 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.

    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
  • 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.

    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
  • 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."

    GPT-6.1 Sol: I’m at the age where “a big weekend” means I went to two stores. Not two stores in the same shopping center. Two separate stores. Moved the car and everything. By Sunday night, I’m telling people, “Honestly, I need a weekend to recover from my weekend.”

    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.

    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
  • 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.

    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
  • 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.

    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
  • 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.

    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 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.

    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
  • 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.

    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
  • 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.

    GPT-6.1 Sol: Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 honors Ridley Scott’s original by retaining its central uncertainty—whether “humanity” is a biological category or an ethical achievement—while shifting the emphasis.

    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.

    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
  • 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.

    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
  • 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.

    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 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.

    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
  • 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.

    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
  • 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.

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

    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
  • 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.

    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
  • 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.

    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
  • 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.

    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

This matchup has more rounds

12+ more head-to-head results. Free. Not a trick.

Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy

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

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 4.6 and GPT-6.1 Sol compared across 54 shared prompts
SpecGLM 4.6GPT-6.1 Sol
Input price$0.4/M tokens$2/M tokens
Output price$1.75/M tokens$10/M tokens
Context window203K tokens1.1M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedSep 2025Sep 2026
At 10M a month$4.00$4.00$20.00$20.00
1M10M100M1B10M tokens

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

Where to run it6 hosts, cheapest first
GLM 4.64 hosts
HostInOutContextUptime
  • VVenicefp4$0.43 in·$1.75 out·198k·99.8% up
  • DDeepInfrafp4$0.50 in·$2.00 out·203k·99.9% up
  • NNovitabf16$0.55 in·$2.20 out·205k·99.4% up
  • Z.aifp4$0.60 in·$2.20 out·203k·99.5% 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 4.6 and GPT-6.1 Sol?

GLM 4.6 is developed by Zhipu AI while GPT-6.1 Sol is developed by OpenAI. GLM 4.6 has a 203K token context window vs GPT-6.1 Sol's 1.1M. 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 GPT-6.1 Sol?

It depends on your use case. GLM 4.6 and GPT-6.1 Sol 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 GPT-6.1 Sol?

GLM 4.6 costs $0.4/M input tokens and GPT-6.1 Sol costs $2/M input tokens. GLM 4.6 is $1.60/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 GPT-6.1 Sol on Rival?

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

More comparisons

Against the newest arrivals

  • GLM 4.6 vs Claude Sonnet 5.5Landed Sep 2026
  • GPT-6.1 Sol vs Solar Mini 4Landed Sep 2026
  • GLM 4.6 vs Qwen3.8 Max PrimeLanded Sep 2026
  • GPT-6.1 Sol vs GLM 5.3 PrimeLanded Sep 2026
  • GLM 4.6 vs Qwen3.8 Omni FlashLanded Sep 2026
  • GPT-6.1 Sol vs Command A+Landed Sep 2026
  • GLM 4.6 vs Claude Opus 5.5Landed Sep 2026
  • GPT-6.1 Sol vs GPT-6 Luna ProLanded Sep 2026

Same lab, same size, long tail

  • GLM 4.6 vs GLM 5.3Same lab
  • GLM 4.6 vs GLM 5.3 FlashSame lab
  • GPT-6.1 Sol vs GPT-6 Astra ProVersion compare
  • GPT-6.1 Sol vs GPT-6 Sol ProSame lab
  • GLM 4.6 vs Granite 4.2 8BNew provider
  • GPT-6.1 Sol vs Grok 3New provider
  • GPT-6.1 Sol vs Grok 3 BetaNew provider
  • GPT-6.1 Sol vs Grok 3 Mini BetaNew provider

Model pages

  • GLM 4.659 outputs, specs and price
  • GPT-6.1 Sol58 outputs, specs and price
Workshop · 150 skills

Build your own version.

Editable skills and working examples for your agent.

Explore $79Free sample
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed