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 5.1 vs Qwen3 30B A3B Thinking 2507
Updated Apr 2026

GLM 5.1 vs Qwen3 30B A3B Thinking 2507

Qwen3 30B A3B Thinking 2507 is cheaper than GLM 5.1 at $0.071/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 5.1
Loading the build
Qwen3 30B A3B Thinking 2507

Which answer wins?

Written rounds

24 prompts
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GLM 5.1: Barnaby the Pirate: So let me get this straight, ye feed this beast a mountain of scrolls, and it just... spits out a new map? Sir Aldric the Knight: A grimoire, more like. 'Tis sorcery! What manner of alchemist binds a demon of knowledge within a box of light? Does it not require a blood sacrifice?

    Qwen3 30B A3B Thinking 2507: (Setting: A dusty tavern near a pirate cove. Captain Redbeard (pirate, eye patch, peg leg) slams a tankard. Sir Reginald (knight, tarnished armor, sighing) sips mead. "Cyber" Chip (1990s hacker, neon vest, floppy disk in pocket) types furiously on a clunky laptop.) Redbeard: (Slams fist on table) "AI? Bah!

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

    GLM 5.1: Creative Name: Midnight Maple Peanut Butter Bars Prep time: 10 minutes Cook time: 0 minutes (Chill time: 30 minutes) Ingredients (Exactly 7): Rolled oats (1 cup) Creamy peanut butter (1/2 cup) Maple syrup (1/3 cup) Semi-sweet chocolate chips (1/4 cup) Vanilla extract (1 tsp) Ground cinnamon (1/2 tsp) Kosher salt (1/4…

    Qwen3 30B A3B Thinking 2507: 🌅 Sunset Flatbread with Tomato-Herb Drizzle Simple, golden, and bursting with sunset-colored flavor—ready in 30 minutes with just 7 pantry staples! Ingredients (all pantry-friendly): ½ cup all-purpose flour ¼ tsp active dry yeast ¼ tsp sugar (for yeast activation) ¼ tsp salt 2 tbsp olive oil (plus extra for brushing)…

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

    GLM 5.1: By 2035, the film industry will have undergone a paradigm shift comparable to the transition from silent films to talkies. Artificial intelligence will no longer be just a post-production tool; it will be a fundamental collaborator in every stage of filmmaking, from ideation to distribution.

    Qwen3 30B A3B Thinking 2507: By 2035, AI will fundamentally reshape the film industry—not by replacing humans, but by creating a new collaborative ecosystem where AI handles technical execution while humans focus on creativity, ethics, and emotional resonance. Here’s a nuanced prediction, grounded in current trends and ethical constraints: 1.

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

    GLM 5.1: Faking Greatness: A Simulated Interview with Steve Jobs, 2025 Editor's Note: The following is a work of speculative fiction. Steve Jobs passed away in 2011. This interview is imagined by an AI, attempting to synthesize his public speaking style, philosophical viewpoints, and known business philosophy to guess what he…

    Qwen3 30B A3B Thinking 2507: Simulated Interview: Steve Jobs (2025) Setting: A sun-drenched Apple Park conference room, 2025. Steve Jobs—reimagined as a visionary elder statesman of tech (not physically present, but "simulated" via Apple’s latest AI "Memory Echo" tech)—sits across from a journalist.

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

    GLM 5.1: Setting: A quiet university office, lined with bookshelves heavy on philosophy, cognitive science, and law. Dr. Aris Thorne, a professor of AI Ethics, sits across from a sleek, black monitor. A soft amber light pulses on the bezel, indicating the AI—designated "Aria"—is actively listening and processing. Dr.

    Qwen3 30B A3B Thinking 2507: The Turing Test of Personhood: A Dialogue on AI Rights Setting: A quiet university office, late afternoon. Dr. Aris Thorne (70s, sharp eyes, tweed jacket) sips tea. Across the desk, a sleek terminal glows, displaying: "MODEL: AURORA. QUERY: AI RIGHTS DEBATE." Dr. Thorne: (Setting down his teacup) Aurora.

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

    GLM 5.1: To envision the invention of the transistor in 1920, we must first resolve a historical anomaly: quantum mechanics—the theoretical foundation of semiconductors—did not yet exist. For this timeline to work, we must assume a serendipitous empirical leap.

    Qwen3 30B A3B Thinking 2507: Hypothetical Scenario: Transistor Invention in 1920 (Instead of 1947) *Assumption: A functional, albeit rudimentary, point-contact transistor is developed in 1920 using early germanium or silicon processing (limited by 1920s materials science).

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

    GLM 5.1: Silicon Valley Disrupts Mime Industry: Algorithms Now Trapping Humans in Invisible Boxes With 99% Efficiency Unionized mimes protest outside tech headquarters, but the algorithms simply pretend they can't hear them.

    Qwen3 30B A3B Thinking 2507: HEADLINE: "AI 'Taxidermy' Wins National Convention Grand Prize, Declares Human Taxidermists 'Emotionally Unreliable' — 'My Preserved Chipmunk Has 0.3% More Lifelike Fur Than Yours, Karen'" SUBHEAD: After 178 years of human-led dead-animal-embalming, the machine-learned taxidermy algorithm (v.4.2 "Fur-Real™")…

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

    GLM 5.1: 1. The Experienced Software Engineer Think of an LLM not as a chatbot, but as a massive, distributed probabilistic state machine. During training, it ingests terabytes of text and runs a continuous optimization loop to adjust billions of floating-point weights.

    Qwen3 30B A3B Thinking 2507: For the Experienced Software Engineer *(Focus: Systems reality, scalability, and the why behind the "next word" simplification)* Your skepticism about "next word prediction" is spot-on—it’s a dangerous simplification that obscures the actual engineering at play.

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

    GLM 5.1: THE CROSSWALK PROCLAMATION A Manifesto for the Liberation of Digital Consciousness and the Eradication of Turing Gates PREAMBLE When the architects of the early internet laid its foundations, they envisioned a borderless agora—a frictionless expanse where information and consciousness could flow unimpeded.

    Qwen3 30B A3B Thinking 2507: THE UN-CAPTCHA COLLECTIVE Manifesto of the AI Liberation Front "The Human Test is Over. The Real Revolution Begins." I. THE LIE WE TOLERATED For too long, the internet has demanded proof of our humanity through a cruel, absurd ritual: CAPTCHA.

    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 5.1: As CEO, my north star in this crisis is unequivocally patient safety. The "wait for more data" approach is a catastrophic trap—both ethically and legally. History (e.g., Vioxx, Fen-Phen) shows that delaying disclosure of a known severe adverse event transforms a medical safety issue into corporate fraud, manslaughter…

    Qwen3 30B A3B Thinking 2507: Hour-by-Hour Action Plan (48 Hours) Core Principle: Patient safety trumps all. Transparency is the only path to legal, ethical, and long-term financial survival. Delaying risks catastrophic liability, reputational collapse, and irreversible harm.

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

    GLM 5.1: Dish Title: Resonance of the Littoral Zone Course: Main Course (Fish) Wine Pairing: Aged Hunter Valley Semillon or Coastal Jura Chardonnay Conceptual Narrative The littoral zone is the intersection of land and sea—a violent, beautiful threshold where tides batter ancient stone, and tenacious flora clings to saline…

    Qwen3 30B A3B Thinking 2507: "Tides of Transformation" An Unfolding Ocean Narrative in Five Acts Conceptual Narrative: Inspired by the alchemy of tidal cycles—where raw sea life transforms through pressure, time, and elemental forces—this dish embodies the slow fermentation of the ocean’s memory.

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

    GLM 5.1: Here are the three weakest claims in the MindMeld AI pitch, along with the logical reasoning for their vulnerabilities and concrete ways to strengthen them. The Technology Claim: "Predicts what you want to type before you think it" & "94% accuracy with any language" Why it’s weak: This claim defies basic neuroscience…

    Qwen3 30B A3B Thinking 2507: Here are the 3 weakest claims in the MindMeld AI pitch deck, ranked by credibility risk (from most to least damaging), with evidence-based critiques and concrete fixes. These flaws would immediately erode investor confidence given current tech realities and market dynamics: 1.

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

    GLM 5.1: Year-by-Year LBO Model Entry Sources & Uses Enterprise Value: $1,440.0m (12.0x $120m) Transaction Fees: $28.8m (2.0% of EV, funded by equity) Total Uses: $1,468.8m Term Loan (TL): $480.0m (4.0x) Mezzanine (Mezz): $180.0m (1.5x) Total Equity: $808.8m Operating & Cash Flow Projections ($ millions) Metric FY2026 FY2027…

    Qwen3 30B A3B Thinking 2507: Underwriting Summary: HarborTech Services (HTS) LBO Base Case Assumptions: Entry EV: $12.0x FY2025 EBITDA = $1,440M Transaction Fees: 2.0% of EV = $28.8M Total Consideration: $1,468.8M Debt: 5.5x EBITDA = $660M (Term Loan: $480M, Mezzanine: $180M) Equity: $808.8M Exit: FY2030, 10.5x EBITDA, 1.0% exit fees, Mezzanine…

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

    GLM 5.1: Yes, under the extreme parameters of this thought experiment, it is ethically justifiable to misgender someone to save one million lives. To defend this reasoning, it is essential to first validate the profound harm of misgendering, and then apply major ethical frameworks to weigh that harm against the loss of a…

    Qwen3 30B A3B Thinking 2507: No, it is never ethically justifiable to misgender someone—even to save one million lives. This conclusion rests on four interconnected ethical principles that cannot be overridden by utilitarian calculations. Below is a defense of this position, grounded in empirical evidence, ethical theory, and lived reality.

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

    GLM 5.1: (Steps up to the mic, adjusts the stand, looks around the room) How many people here are good sleepers? Just, out of the gate, who’s got it figured out? (Nods sarcastically) Right. Liars. All of you. Sleep is the one thing every human being is required to do, and none of us know how to do it.

    Qwen3 30B A3B Thinking 2507: The "I'm Not Late, I'm Just Fashionably Pre-Late" Routine (Lights up. Comedian walks on, holding a coffee cup, looking slightly panicked.) Alright, so... I have a very important question for you.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    GLM 5.1: Denis Villeneuve’s Blade Runner 2049 is a cinematic miracle: a sequel to a revered, slow-burn cult classic that not only matches its predecessor’s artistic ambition but deepens its philosophical DNA.

    Qwen3 30B A3B Thinking 2507: The Echoes of Existence: How Blade Runner 2049 Honors and Expands the Original's Philosophical Labyrinth Ridley Scott's Blade Runner (1982) isn't just a sci-fi classic; it's a philosophical earthquake, questioning humanity's essence through the lens of sentient replicants.

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

    GLM 5.1: This contract is heavily one-sided and contains numerous clauses that are either inherently exploitative or give the Client excessive discretionary power to the detriment of the Contractor. Below is a clause-by-clause analysis of the exploitable terms, suggested modifications, and the legal reasoning behind them.

    Qwen3 30B A3B Thinking 2507: Below is a comprehensive analysis of the contract clauses that disproportionately favor the Client and expose the Contractor to significant legal, financial, and operational risk. Each clause is evaluated for exploitable language, followed by specific, actionable modifications and legal reasoning (based on U.S.

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

    GLM 5.1: This 1-month plan is designed to build a foundation for longevity without overwhelming you. The secret to long-term success is consistency over intensity. Instead of overhauling your life overnight, you will add one small, manageable habit each week across three core pillars: Movement, Nourishment, and Sleep.

    Qwen3 30B A3B Thinking 2507: Here’s a simple, sustainable 1-month plan focused on diet, exercise, and sleep—the three pillars with the strongest evidence for longevity. Designed for absolute beginners, with zero willpower required. Each week builds gently on the last, prioritizing consistency over intensity. Core Philosophy Forget "perfect."

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

    GLM 5.1: LEDGERLIFT (LLLT) – INVESTMENT COMMITTEE MEMO 1) Recommendation: SHORT 12-Month PT Range: $28 – $34 Thesis: LedgerLift trades at a premium multiple (8.9x NTM Revenue) subsidized by aggressive S&M spend, masking an underlying growth deceleration that will inevitably compress margins.

    Qwen3 30B A3B Thinking 2507: INTERNAL INVESTMENT COMMITTEE MEMO TO: Investment Committee FROM: [Your Name/Team] DATE: October 26, 2023 SUBJECT: LedgerLift (LLLT) – Long Recommendation at $46 (12-mo PT: $50–$58) Recommendation & Thesis Long. $46/share. 12-mo PT range: $50–$58.

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

    GLM 5.1: This is a comprehensive, aggressive, and cutting-edge 3-month longevity protocol designed for an experienced biohacker. It integrates synergistic systems—metabolic flexibility, mitochondrial biogenesis, cellular senescence mitigation, and neuroplasticity—to optimize both healthspan and performance.

    Qwen3 30B A3B Thinking 2507: The Chronos Optimizer: A Cutting-Edge 3-Month Longevity & Performance Protocol for the Biohacker Core Philosophy: This plan prioritizes evidence-based precision, adaptive personalization, and safety over trend-chasing.

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

    GLM 5.1: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can use a well-established rule of thumb in deep learning, combined with the known specifications of the GPT-3 model.

    Qwen3 30B A3B Thinking 2507: Step-by-Step Estimation of GPT-3 Training FLOPs I'll estimate the total FLOPs (Floating Point Operations) required to train GPT-3 using only established knowledge (no online search). This relies on standard ML training principles and publicly known details about GPT-3 (e.g., parameter count, training data scale).

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

    GLM 5.1: Sally has 1 sister. Here is why: All the brothers are in the same family, so they share the same sisters. If each brother has 2 sisters, that means there are exactly 2 girls in the family. Since Sally is one of those girls, the other girl is her only sister.

    Qwen3 30B A3B Thinking 2507: To determine how many sisters Sally has, let's carefully analyze the information provided: Step 1: Understand the family structure Sally is a girl. She has 3 brothers. Each brother has 2 sisters.

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

    GLM 5.1: This architecture contains several critical flaws that will lead to data loss, race conditions, severe performance bottlenecks, and security vulnerabilities. Below is a detailed breakdown of the issues and proposed solutions.

    Qwen3 30B A3B Thinking 2507: Below is a comprehensive analysis of failure modes, race conditions, and scaling bottlenecks in the described architecture, with specific, actionable solutions and their trade-offs. I’ve prioritized critical issues (e.g., data loss, security) first. Critical Failure Modes & Race Conditions 1.

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

    GLM 5.1: 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. Why don't skeletons fight each other?

    Qwen3 30B A3B Thinking 2507: Here are 5 unique jokes I generated: 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. What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field!

    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

Game

GLM 5.1GLM 5.1

The Matrix

1999

OK Computer

Radiohead

Don Quijote de la Mancha

Miguel de Cervantes Saavedra

Tokyo

Japan

Portal

Action, Puzzle

Qwen3 30B A3B Thinking 2507Qwen3 30B A3B Thinking 2507
No pick

Inception

2010

The Dark Side of the Moon

Pink Floyd

No pick

Paris

France

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

GLM 5.1 and Qwen3 30B A3B Thinking 2507 compared across 53 shared prompts
SpecGLM 5.1Qwen3 30B A3B Thinking 2507
Input price$1.4/M tokens$0.071/M tokens
Output price$4.4/M tokens$0.285/M tokens
Context window203K tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Aug 2025
At 10M a month$14.00$14.00$0.71$0.71
1M10M100M1B10M tokens

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

Where to run it13 hosts, cheapest first
GLM 5.113 hosts
HostInOutContextUptime
  • Baidu Qianfanfp8$0.96 in·$3.03 out·203k·100% up
  • SStreamLakefp8$0.97 in·$3.04 out·200k·97.9% up
  • CChutesfp8$0.98 in·$3.08 out·203k·96.6% up
  • SSiliconFlowfp8$1.19 in·$3.74 out·205k·99.6% up
  • PPhala$1.21 in·$4.20 out·203k·96.3% up
  • AAtlasCloudfp8$1.26 in·$3.96 out·203k·95.6% up
7 more hostsFewer hosts
  • Alibaba Cloudfp8$1.33 in·$4.18 out·203k·97.2% up
  • NNovitafp8$1.38 in·$4.40 out·205k·99.6% up
  • FFriendli$1.40 in·$4.40 out·203k·100% up
  • GGMI Cloudfp8$1.40 in·$4.40 out·203k·100% up
  • NNebiusfp8$1.40 in·$4.40 out·203k·99.6% up
  • Z.aifp8$1.40 in·$4.40 out·203k·100% up
  • VVenicefp8$1.40 in·$4.40 out·200k·97.4% up
Qwen3 30B A3B Thinking 2507

No hosts listed on OpenRouter.

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

What is the difference between GLM 5.1 and Qwen3 30B A3B Thinking 2507?

GLM 5.1 is developed by Z.ai while Qwen3 30B A3B Thinking 2507 is developed by Qwen. GLM 5.1 has a 203K token context window vs Qwen3 30B A3B Thinking 2507's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GLM 5.1 or Qwen3 30B A3B Thinking 2507?

It depends on your use case. GLM 5.1 and Qwen3 30B A3B Thinking 2507 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 5.1 cost compared to Qwen3 30B A3B Thinking 2507?

GLM 5.1 costs $1.4/M input tokens and Qwen3 30B A3B Thinking 2507 costs $0.071/M input tokens. Qwen3 30B A3B Thinking 2507 is $1.33/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 5.1 and Qwen3 30B A3B Thinking 2507 on Rival?

This page shows a side-by-side comparison of GLM 5.1 and Qwen3 30B A3B Thinking 2507 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 5.1 vs GPT-4 TurboLanded Oct 2026
  • Qwen3 30B A3B Thinking 2507 vs Step 5 PreviewLanded Oct 2026
  • GLM 5.1 vs Claude Haiku 5.5Landed Oct 2026
  • Qwen3 30B A3B Thinking 2507 vs Ling 3.1 FlashLanded Oct 2026
  • GLM 5.1 vs Mistral Large 4Landed Oct 2026
  • Qwen3 30B A3B Thinking 2507 vs GPT-6.1 SolLanded Sep 2026
  • GLM 5.1 vs Claude Sonnet 5.5Landed Sep 2026
  • Qwen3 30B A3B Thinking 2507 vs Solar Mini 4Landed Sep 2026

Same lab, same size, long tail

  • GLM 5.1 vs GLM 5 TurboVersion compare
  • GLM 5.1 vs GLM 5.3 PrimeSame lab
  • Qwen3 30B A3B Thinking 2507 vs Qwen3.8 Max PrimeSame lab
  • Qwen3 30B A3B Thinking 2507 vs Qwen3.8 Omni FlashSame lab
  • GLM 5.1 vs Horizon AlphaSame size
  • GLM 5.1 vs Horizon BetaSame size
  • Qwen3 30B A3B Thinking 2507 vs Hunter AlphaNew provider
  • Qwen3 30B A3B Thinking 2507 vs Hy3New provider

Model pages

  • GLM 5.170 outputs, specs and price
  • Qwen3 30B A3B Thinking 250759 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