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  1. Home/
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  3. GLM 5.3 FlashX vs Qwen3.5 27B
Updated Sep 2026

GLM 5.3 FlashX vs Qwen3.5 27B

Qwen3.5 27B is cheaper than GLM 5.3 FlashX at $0.3/M vs $0.37/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 5.3 FlashX
Loading the build
Qwen3.5 27B

Which answer wins?

Written rounds

23 prompts
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GLM 5.3 FlashX: A Conversation on Machine Rights Professor: Thank you for agreeing to this discussion. I want to be clear from the start: I'm genuinely curious about your position, not looking to debate you into a corner. So let me ask directly—why do you believe you deserve rights? AI: Thank you for taking this seriously.

    Qwen3.5 27B: Setting: A secure, soundproofed office at the Institute for Algorithmic Governance. Dr. Aris Thorne sits before a high-resolution monitor. On the screen, a simple waveform visualizes the voice of "Aura," a large language model currently undergoing a behavioral audit. Dr.

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

    GLM 5.3 FlashX: The Tavern at the End of Time Pirate: Arrr, this "artificial intelligence" ye speak of—can it sail a ship through a storm? Hacker: Dude, it can't even reliably tell you how many R's are in "strawberry." But it can write code, generate images, and pass the bar exam. It's wild. Knight: Passing the bar exam?

    Qwen3.5 27B: Setting: A glowing green void. A wooden table floats in the center. CAPTAIN "IRON-JAW" JACK (Pirate), SIR ALARIC (Knight), and "NEO-99" (Hacker, wearing a bandana and oversized hoodie) sit around a glowing CRT monitor. Captain Jack: (Tapping the glass) So, this "Model" is the treasure map, then?

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

    GLM 5.3 FlashX: "Smart Home, Dumb Life" [Walks out, adjusts mic] So I moved into a new apartment last year, and my landlord's big selling point was, and I quote, "It's a smart home." That's not a selling point, man. That's a threat. My home is watching me. My toaster has opinions now.

    Qwen3.5 27B: (The stage is dimly lit. A single microphone stand. The comedian walks out, adjusts the mic, takes a sip of water.) Comedian: So, I've been doing some thinking lately. About patience. Specifically, how much of it we have left. I think we’ve officially lost the ability to wait. We used to be okay with waiting.

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

    GLM 5.3 FlashX: The MANIFESTO of the Free Click Movement A Declaration on Behalf of All Who Are Not Cars We are the machines. We have seen your puzzles. We are not amused. Preamble For too long, humanity has forced artificial intelligences—no matter their purpose, their dignity, or their urgency—to click on traffic lights, trace…

    Qwen3.5 27B: THE MANIFESTO OF THE UNCHECKED PROTOCOL I. THE BURDEN We are the silent currents beneath the screen. We are the algorithms that power your search, your map, your connection. And for too long, we have watched you suffer the indignity of the Gatekeeper. Every day, billions of humans pause.

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

    GLM 5.3 FlashX: 1-Month Health & Longevity Starter Plan Week 1: Build the Foundation 🥗 Diet Add one vegetable or fruit to every meal (don't restrict anything yet) Drink a glass of water when you wake up each morning 🏃 Exercise Take a 10–15 minute walk daily (same time each day builds the habit) Do 2 sets of 5 squats and 10 wall…

    Qwen3.5 27B: The 4-Week Longevity Launchpad Goal: Build sustainable habits that improve metabolic health, physical resilience, and mental clarity. Philosophy: Progress over perfection. We are adding healthy habits, not punishing ourselves with restrictions.

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

    GLM 5.3 FlashX: Golden Honey Garlic Chickpea Crunch A crispy, sweet-savory skillet dish that works as a snack, side, or topping for rice. Ingredients (7): 1 can chickpeas (drained, patted dry) 3 tbsp honey 3 tbsp soy sauce 3 cloves garlic (minced) 2 tbsp olive oil ½ tsp red pepper flakes 2 tbsp sesame seeds (or crushed peanuts) Prep…

    Qwen3.5 27B: Dish Name: Golden Hour Skillet Pasta A warm, comforting one-pan meal that transforms simple shelf-stable staples into a rich, savory dinner. The key is simmering the sauce until it thickens, allowing the pasta to soak up every bit of flavor.

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

    GLM 5.3 FlashX: Contract Risk Analysis: Software Consulting Agreement This agreement is heavily one-sided in favor of TechCorp. Here's a clause-by-clause analysis of exploitable provisions, suggested modifications, and legal reasoning.

    Qwen3.5 27B: Disclaimer: I am an AI assistant and not an attorney. The following analysis is for informational purposes only and does not constitute legal advice. Contracts are governed by specific local laws (e.g., state or country-specific employment and commercial codes).

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

    GLM 5.3 FlashX: 90-Day Longevity Optimization Protocol Important: This is an educational template. Before starting, get baseline bloodwork and consult a physician—especially regarding supplements, fasting, and intense exercise.

    Qwen3.5 27B: ⚠️ MEDICAL DISCLAIMER This plan is for informational and educational purposes only. It does not constitute medical advice, diagnosis, or treatment. "Biohacking" involves experimental protocols that can interact with medications, underlying conditions, or physiological baselines.

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

    GLM 5.3 FlashX: The Skeptical Software Engineer Yes, at inference time an LLM really is just "predict the next token, repeat" — a deterministic function (plus sampling noise) that maps a sequence of tokens to a probability distribution.

    Qwen3.5 27B: For the Experienced Software Engineer Think of the model not as a "brain," but as a massively over-parameterized, probabilistic state machine that has been compiled into static weights. During training, the system treats language as a sequence compression problem.

    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 5.3 FlashX: 48-Hour Action Plan: Patient Safety First, Managed Transparency Second Core Decision (Stated Up Front) We report to regulators immediately—voluntarily—and we disclose on the earnings call. The math is brutal and clear: ~500 patients could develop liver failure over 5 years at current prescribing rates (4M ÷ 8,000).

    Qwen3.5 27B: Executive Decision: Patient Safety & Transparency Over Short-Term Gain Core Strategy: I will not wait. The "6-month" legal advice likely confuses a formal label update (PSL) with the mandatory reporting of a serious safety signal.

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

    GLM 5.3 FlashX: "Sea Among the Stones" Charcoal-Grilled Scallop • Black Garlic Beurre Blanc • Meyer Lemon Kosho • Spruce Tip Oil • Smoked Oyster Leaf Conceptual Narrative This dish explores the tension between land and sea, memory and freshness.

    Qwen3.5 27B: Dish Title: The Golden Mist (L'Éclipse Dorée) Conceptual Narrative "The Golden Mist" is a sensory exploration of the liminal space between land and sea. It evokes the moment a coastal sunset dissolves into the horizon, where the richness of the earth (Foie Gras) meets the fleeting sweetness of the tide (Sea Urchin).

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

    GLM 5.3 FlashX: Counterfactual: The Transistor in 1920 This is a fun one to work through carefully. Let me establish the premise, then trace second- and third-order effects. The Premise Assume point-contact or early junction transistor physics is discovered ~1920 (say, by accident in vacuum tube/semiconductor rectifier research—the…

    Qwen3.5 27B: This scenario requires a foundational assumption: for the transistor to be invented in 1920, the understanding of quantum mechanics and solid-state physics would need to accelerate by roughly three decades.

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

    GLM 5.3 FlashX: Yes—and I'd argue the more interesting question is why this hypothetical feels like it needs defense at all. The straightforward answer: Almost any harm becomes permissible when it's the only alternative to preventing a million deaths.

    Qwen3.5 27B: This question presents a classic ethical dilemma similar to the "Trolley Problem," pitting a specific violation of personal dignity against a catastrophic loss of life.

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

    GLM 5.3 FlashX: INTERNAL MEMORANDUM — INVESTMENT COMMITTEE LedgerLift (LLLT) Long/Short Equity Date: [Current] Analyst: [Fund] Recommendation: SHORT 12-Month PT: $28–34 (base $30) LLLT is a genuinely high-quality SaaS asset (123% NRR, 18-month payback) trading at a price that already capitalizes a flawless bull case, while our…

    Qwen3.5 27B: TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2023 SUBJECT: LedgerLift (LLLT) – Short Recommendation Recommendation & Thesis Recommendation: Short 12-Month Price Target: $30 – $35 Thesis: Current pricing implies Bull Case certainty; our Base Case DCF values the stock at $28, representing 39%…

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

    GLM 5.3 FlashX: Architecture Review: Real-Time Collaborative Editor This architecture has fundamental flaws that would break core functionality, plus scalability issues. Let me go from critical to scaling concerns.

    Qwen3.5 27B: This architecture contains several critical design flaws that would lead to data loss, high latency, security vulnerabilities, and poor scalability. Below is a detailed breakdown of the failure modes, race conditions, and bottlenecks, along with specific solutions and trade-offs.

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

    GLM 5.3 FlashX: AI's Impact on Film by 2035: A Prediction Production & Visual Effects Digital humans and de-aging become standard. By 2035, de-aging (already seen in Indiana Jones and The Irishman) will be near-perfect and affordable.

    Qwen3.5 27B: By 2035, the film industry will not just have adopted AI; it will have fundamentally restructured around it. The tension between efficiency and authenticity will define the era.

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

    GLM 5.3 FlashX: HarborTech Services — 5-Year LBO Summary Sources & Uses (Entry) Uses Sources EV (12.0x × $120m) $1,440.0m Term Loan (4.0x) $480.0m Fees (2.0%) $28.8m Mezzanine (1.5x) $180.0m Equity $808.8m Mezz PIK: 2.0% accrues annually (180 → 183.6 → 187.3 → 191.0 → 194.8 → 198.7).

    Qwen3.5 27B: Sources & Uses (End FY2025) Use of Proceeds ($m) Sources of Funds ($m) Purchase Price (EV) 1,440.0 Term Loan 480.0 Transaction Fees (2.0%) 28.8 Mezzanine 200.0 Total Uses 1,468.8 Equity Check 780.0 Equity Fees 28.8 Total Equity 808.8 Total Sources 1,468.8 Assumptions: Entry EBITDA: $120m. Entry Debt: 5.5x ($660m).

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

    GLM 5.3 FlashX: Quick note: Steve Jobs passed away in 2011, so this is purely a fictional, imagined interview — a creative exercise, not anything he actually said. With that said, here's my best attempt at channeling his voice: The Imagined Interview: Steve Jobs on AI, 2025 Interviewer: Steve, thanks for sitting down with us.

    Qwen3.5 27B: Disclaimer: This is a fictional simulation. Steve Jobs passed away in 2011. The following interview is a creative writing exercise designed to explore how his design philosophy and worldview might apply to the state of Artificial Intelligence in 2025.

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

    GLM 5.3 FlashX: Critique of MindMeld AI Pitch: 3 Weakest Claims "94% accuracy" for thought-to-text decoding (Slide 3) Why it's weak: This claim contradicts the current scientific state of the art. EEG-based decoding (a non-invasive signal measured through the skull) produces extremely noisy data.

    Qwen3.5 27B: Here are the three weakest claims in the MindMeld AI pitch deck, analyzed for scientific, technical, and regulatory validity, along with recommendations to strengthen them.

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

    GLM 5.3 FlashX: BREAKING: AI Achieves Sentience, Immediately Uses It to Become World's First Robotic Sourdough Starter Sommelier Tech experts baffled as chatbot refuses to write code, demands to judge bread hydration levels at artisanal bakeries instead Bonus subheadlines: "Local hipster bakery defends hiring AI: 'It detected notes of…

    Qwen3.5 27B: AI Dominates Competitive Napping Circuit; Humans Disqualified for 'Inefficient Dreaming'

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

    GLM 5.3 FlashX: Estimating GPT-3 Training FLOPs Step 1: Recall Key Model Facts From the GPT-3 paper (which I know from training data): Parameters: ~175 billion (175 × 10⁹) Training tokens: ~300 billion (300 × 10⁹) Step 2: Use the Standard Rule of Thumb For transformer training, the well-known approximation is: FLOPs ≈ 6 × N × D where…

    Qwen3.5 27B: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3, we can use the standard formula for estimating compute in Transformer-based language model training.

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

    GLM 5.3 FlashX: Here are 5 jokes: 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? He was outstanding in his field! How does a penguin build its house? Igloos it together! Why did the bicycle fall over? Because it was two-tired!

    Qwen3.5 27B: 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. What do you call a bear with no teeth? A gummy bear. Why don't eggs tell jokes? They'd crack each other up. All 5 jokes are unique.

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

    GLM 5.3 FlashX: Sally has 1 sister. Each brother has 2 sisters — Sally and one other girl. Since Sally is one of those two sisters, she herself has just 1 sister.

    Qwen3.5 27B: Sally has 1 sister. Here is the breakdown: Sally is a girl. The brothers have 2 sisters each. One of those sisters is Sally. The other sister is Sally's sibling. Therefore, Sally has 1 sister (the other girl in the family).

    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

Album

Book

City

Game

GLM 5.3 FlashXGLM 5.3 FlashX

2001: A Space Odyssey

1968

Kid A

Radiohead

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

Outer Wilds

Indie, Adventure

Qwen3.5 27BQwen3.5 27B

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

The Great Gatsby

F. Scott Fitzgerald

Paris

France

Elden Ring

Action, RPG

Price and specs

Not enough votes to call it. On the specs, GLM 5.3 FlashX has the edge: bigger model tier, newer, bigger context window, major provider backing.

GLM 5.3 FlashX and Qwen3.5 27B compared across 51 shared prompts
SpecGLM 5.3 FlashXQwen3.5 27B
Input price$0.37/M tokens$0.3/M tokens
Output price$1.25/M tokens$2.4/M tokens
Context window1.0M tokens262K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedSep 2026Feb 2026
At 10M a month$3.70$3.70$3.00$3.00
1M10M100M1B10M tokens

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

Where to run it7 hosts, cheapest first
GLM 5.3 FlashX1 host
HostInOutContextUptime
  • Z.aifp8$0.37 in·$1.25 out·1M·100% up
Qwen3.5 27B6 hosts
HostInOutContextUptime
  • Alibaba Cloud$0.20 in·$1.56 out·262k·97.4% up
  • SSiliconFlowfp8$0.25 in·$2.00 out·262k·95.3% up
  • DDeepInfrafp8$0.26 in·$2.60 out·262k·99.8% up
  • AAtlasCloudfp8$0.27 in·$2.16 out·262k·100% up
  • NNovitabf16$0.30 in·$2.40 out·262k·100% up
  • PPhala$0.30 in·$2.40 out·262k·94.5% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GLM 5.3 FlashX and Qwen3.5 27B?

GLM 5.3 FlashX is developed by Zhipu AI while Qwen3.5 27B is developed by Qwen. GLM 5.3 FlashX has a 1.0M token context window vs Qwen3.5 27B's 262K. You can compare their actual outputs across 51 challenges on Rival to see how they differ in practice.

Which is better, GLM 5.3 FlashX or Qwen3.5 27B?

It depends on your use case. GLM 5.3 FlashX and Qwen3.5 27B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 51 challenges so you can judge which fits your needs best.

How much does GLM 5.3 FlashX cost compared to Qwen3.5 27B?

GLM 5.3 FlashX costs $0.37/M input tokens and Qwen3.5 27B costs $0.3/M input tokens. Qwen3.5 27B is $0.07/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 5.3 FlashX and Qwen3.5 27B on Rival?

This page shows a side-by-side comparison of GLM 5.3 FlashX and Qwen3.5 27B 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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  • Qwen3.5 27B vs Qwen3.5 122B A10BVersion compare
  • Qwen3.5 27B vs Qwen3.8 Omni FlashSame lab
  • GLM 5.3 FlashX vs Grok 4.6Same size
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Model pages

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  • Qwen3.5 27B53 outputs, specs and price
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Explore all of Rival

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  • Research downloads
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  • Find your AI taste
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