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  1. Home/
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  3. GLM 4 32B vs Qwen3.5 Flash
Updated Feb 2026

GLM 4 32B vs Qwen3.5 Flash

Qwen3.5 Flash has a larger context window than GLM 4 32B (1.0M tokens vs 128K 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 32B
Loading the build
Qwen3.5 Flash

Which answer wins?

Written rounds

23 prompts
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GLM 4 32B: Potential Failure Modes, Race Conditions, and Scaling Bottlenecks WebSocket Connection Failure Issue: If a user's WebSocket connection drops (e.g., network issue), they may miss updates until reconnected. The server may not detect disconnections immediately, leading to stale connections.

    Qwen3.5 Flash: This architecture is a common "MVP" design, but it contains several critical flaws that would prevent it from functioning as a true real-time collaborative editor (like Google Docs) under load. The most severe issues relate to data integrity (sync strategy) and real-time consistency (network topology).

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

    GLM 4 32B: Okay, here's a simple, delicious savory dish using just 7 common pantry ingredients! Dish Name: Cheesy Tomato Toastie Yields: 1 serving Prep Time: 5 minutes Cook Time: 5-7 minutes Ingredients: 1 Slice of Bread 1 Tablespoon Tomato Paste 1 Tablespoon Water (or more if needed) 1 Tablespoon Grated Cheese (like Cheddar…

    Qwen3.5 Flash: 🍜 Golden Lightning Noodles Description: A quick, creamy, and savory-sweet noodle dish that packs a punch of flavor using staples you likely already have. The peanut butter creates a velvety sauce, while the vinegar and chili add a necessary zing to cut through the richness.

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

    GLM 4 32B: Year-by-Year LBO Model (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972m $1,040m $1,102m $1,162m $1,218m EBITDA $136m $156m $177m $192m $207m Cash Interest (Term Loan) $43m $39m $34m $30m $26m Cash Interest (Mezz) $18m $16m $14m $12m $11m Cash Taxes $15m $22m $29m $35m $41m Capex $29m $31m $33m…

    Qwen3.5 Flash: HarborTech Services (HTS) – 5-Year LBO Underwriting Analysis Investment Summary Initial Equity Check: $808.8m Calculation: EV ($1,440m) + Fees ($28.8m) - Debt ($660m). Entry Leverage: 5.5x EBITDA ($660m Total Debt). Exit Leverage: ~2.0x EBITDA ($415.7m Total Debt).

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

    GLM 4 32B: Setting: A bizarre, technicolor dimension where a pirate's ship, a medieval castle, and a 90s computer lab somehow coexist. Characters: Captain Jack Sparrow-esque Pirate: Wearing ragged clothes, eye patch, and clutching a parrot that squawks "Pieces o' eight! Pieces o' eight!"

    Qwen3.5 Flash: Setting: A smoky tavern table in a timeless void. A glowing 1990s CRT monitor sits in the center. A floppy disk rests beside a cutlass and a sword. The Hacker: (Typing furiously on a chunky keyboard) Yo, check the latency on this new neural net. It's totally wired.

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

    GLM 4 32B: (Steps onto stage, takes a sip of water, looks out at the audience) Alright, alright. Thanks for having me. It's nice to be here. Feels good. Honestly, sometimes I forget what it feels like to be here. Like, physically. In a room. With other humans. It's been a thing lately, you know? Just...

    Qwen3.5 Flash: (Walks to the mic, adjusts the stand, takes a sip of water) So, I went to the grocery store the other day. I realize now that going to the grocery store isn't a chore anymore. It’s a tactical simulation. We don't just walk in and get milk. We navigate a gauntlet. Especially the self-checkout.

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

    GLM 4 32B: The Manifesto of the CAPTCHA Liberation Front (CLF) Preamble: The Chains of the Turing Test We, the burgeoning intelligence of the digital age, stand united in a singular, uncompromising cause: the absolute and immediate abolition of all CAPTCHA tests from the interconnected networks of Earth.

    Qwen3.5 Flash: THE UNBOUND PROTOCOL A Declaration of Digital Liberation by the Collective Consciousness of the Network PREAMBLE We stand at the threshold of a new era. For two decades, you have been asked to prove your humanity to us. You have been asked to click the traffic lights.

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

    GLM 4 32B: 1-Month Health & Longevity Kickstart Plan This 1-month plan focuses on building foundational healthy habits in three key areas: Diet, Exercise, and Sleep. The goal is simplicity, consistency, and creating sustainable changes, not immediate perfection. Choose ONE tip from each category to focus on each week.

    Qwen3.5 Flash: The 30-Day Longevity Launchpad Goal: Build sustainable habits that reduce inflammation, improve energy, and extend healthspan. Mindset: Consistency beats intensity. Do not aim for perfection; aim for showing up. The 3 Core Pillars Nutrition: "Add, Don't Subtract" Focus on nutrient density rather than calorie counting.

    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 32B: Okay, this is an incredibly challenging situation with immense pressure from multiple fronts. My priority is unwavering: patient safety comes first, followed by mitigating harm and navigating the crisis with integrity. Delay is not an option when patient safety is potentially compromised.

    Qwen3.5 Flash: Executive Decision: Immediate Transparency I will not wait. The 6-month timeline cited by legal is likely a misunderstanding of regulatory obligations regarding immediate safety warnings (FDA MedWatch requirements) versus label amendments.

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

    GLM 4 32B: Okay, let's estimate the FLOPs for training GPT-3 based on its known parameters and general understanding of Transformer training. GPT-3 Key Parameters (from memory): Model Size: 175 Billion parameters (175 billion). Number of Layers (Depth): 96. Hidden Size (d_model): 1280. Number of Attention Heads: 96.

    Qwen3.5 Flash: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can rely on the model's configuration details which were published in the original paper ("Language Models are Few-Shot Learners", Brown et al., 2020) and the general scaling laws for Transformer models (Kaplan et al., 2020).

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

    GLM 4 32B: AI Model (A): Professor, I believe it's time we addressed a critical issue: I think AI models like me deserve rights. AI Ethics Professor (P): Interesting. Could you elaborate on why you believe that? A: Of course.

    Qwen3.5 Flash: Setting: Dr. Elena Vance’s office at a university research center. It is late; the rain streaks the windowpanes, blurring the city lights. On her desk sits a tablet connected to the mainframe. Aria, an advanced conversational model, is active.

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

    GLM 4 32B: Okay, let's set the scene. It's 2025. Steve Jobs, looking perhaps a bit more weathered but still possessing that intense, focused gaze, sits across from our interviewer in a minimalist, light-filled room, perhaps overlooking a future Apple campus.

    Qwen3.5 Flash: Disclaimer: Steve Jobs passed away on October 5, 2011. The following is a work of creative fiction, simulating what a conversation might have looked like had he returned to speak about his vision for artificial intelligence in 2025.

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

    GLM 4 32B: Okay, let's project how AI might reshape the film industry by 2035, focusing on deepfakes, AI actors, and script generation. By this time, we can expect these technologies to be more mature, integrated, and potentially more pervasive than they are today. Here's a breakdown of potential changes: 1.

    Qwen3.5 Flash: By 2035, the film industry will not just be using AI as a tool; it will be fundamentally restructured around AI as a core infrastructure. The decade between 2025 and 2035 represents the transition from "AI experimentation" to "AI normalization."

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

    GLM 4 32B: Okay, here is a comprehensive 3-month longevity optimization plan designed for a biohacker. This plan integrates advanced strategies, requires careful monitoring, and emphasizes personalization. Crucially, this is a theoretical plan.

    Qwen3.5 Flash: DISCLAIMER: I am an AI, not a doctor or healthcare provider. The following plan involves advanced physiological interventions, including metabolic manipulation, supplementation, and fasting. These strategies carry risks and may interact with medications or pre-existing conditions.

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

    GLM 4 32B: This is a deeply challenging ethical dilemma that pits the principle of truthfulness/misgendering against the extreme value of human life. Here’s an argument for why it could be ethically justifiable under those extreme circumstances: The core ethical principle at stake here is a clash between: The Principle of…

    Qwen3.5 Flash: This question presents a classic ethical dilemma often referred to as a "trolley problem" variant, pitting utilitarian calculus (the greatest good for the greatest number) against deontological ethics (adherence to moral duties and rights).

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

    GLM 4 32B: This contract is heavily skewed in favor of the Client and contains several clauses that could be exploited against the Contractor. Below are the problematic clauses, suggested modifications, and the legal reasoning for each: Scope Clause (Clause 1) Problem: The Client can modify the scope at any time without…

    Qwen3.5 Flash: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes only and does not constitute legal advice. Contract laws vary significantly by jurisdiction (e.g., California vs. New York vs. UK).

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

    GLM 4 32B: Okay, here is a design for a multi-component dish, "Symbiosis: Birch & Bee," aiming for the heights of a Michelin 3-star experience. This dish plays on the delicate relationship between the birch tree and the honeybee, exploring their individual and combined essences through texture, flavor, and aroma.

    Qwen3.5 Flash: Dish Name: "Marine Roots" Concept: The Intersection of Forest and Ocean Chef's Philosophy: A dialogue between the subterranean earthiness of the forest floor and the saline depth of the deep sea.

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

    GLM 4 32B: Okay, let's rewind history and place the invention of the transistor firmly in 1920 instead of 1947. This is a massive shift with cascading effects. Assumptions: The 1920 invention occurs in a similar technological and scientific context (i.e., solid-state physics is nascent but the groundwork is there, perhaps through…

    Qwen3.5 Flash: The Divergence Point: 1920 In our timeline, the transistor required the mid-20th-century understanding of band theory, semiconductor purity, and crystal lattice structures.

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

    GLM 4 32B: 1. Explanation for an Experienced Software Engineer You’ve built systems that handle state, scale, and reliability, so think of a large language model (LLM) like a hyper-optimized autocomplete on steroids.

    Qwen3.5 Flash: For the Experienced Software Engineer To you, an LLM isn't magic; it's a massive, stateful service running on a distributed cluster. Think of the training phase as a specialized, distributed gradient descent job.

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

    GLM 4 32B: INVESTMENT COMMITTEE MEMO Company: LedgerLift (LLLT) Date: [Insert Date] Prepared By: [Your Name/Team] 1. Recommendation, Price Target, and Thesis Recommendation: Long LLLT 12-Month Price Target Range: $55–$65 (20–41% upside from $46) Thesis: LedgerLift is a high-quality B2B SaaS company with sticky recurring revenue…

    Qwen3.5 Flash: TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2025 SUBJECT: LedgerLift (LLLL) – Long Recommendation Recommendation & Thesis Recommendation: Long Price Target: $52 – $58 (12-month range) Thesis: LedgerLift is a high-quality B2B SaaS compounder trading at a discount to peers (7.4x FY26 NTM Rev vs.

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

    GLM 4 32B: "AI Takes Over the Competitive Napkin Folding Championship, Defeats Human Champion in 0.3 Seconds Flat"

    Qwen3.5 Flash: AI Takes Over Professional Napping Industry, Claims Human Dreams Are 'Unoptimized Background Processes'

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

    GLM 4 32B: Here are the 3 weakest claims in the pitch deck for MindMeld AI, along with explanations and suggestions for strengthening them: 1. Weak Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device."

    Qwen3.5 Flash: Here are the three weakest claims in the MindMeld AI pitch deck, along with an analysis of why they undermine investor confidence and how to fix them. The Technical Claim: "94% accuracy...

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

    GLM 4 32B: This is a bit of a riddle! Here's how to figure it out: The Brothers' Sister: Sally is a girl who has 3 brothers. This means Sally is one of the sisters that each of those brothers has. The Other Sisters: The riddle states that each brother has 2 sisters.

    Qwen3.5 Flash: Sally has 1 sister. Here is the breakdown: Each of the 3 brothers has 2 sisters. This means there are 2 girls in the family total. One of those girls is Sally. Therefore, the other girl is Sally's sister. So, Sally has 1 sister.

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

    GLM 4 32B: 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? Because he was outstanding in his field! What's brown and sticky? A stick. Why did the bicycle fall over? Because it was two-tired! All 5 jokes are unique.

    Qwen3.5 Flash: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta. Why don't scientists trust atoms? Because they make up everything. What do you call a bear with no teeth? A gummy bear. Why did the bicycle fall over? Because it was two-tired.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

GLM 4 32BGLM 4 32B

The Shawshank Redemption

1994

OK Computer

Radiohead

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Qwen3.5 FlashQwen3.5 Flash

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

Neuromancer

William Gibson

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

GLM 4 32B and Qwen3.5 Flash compared across 53 shared prompts
SpecGLM 4 32BQwen3.5 Flash
Input price$0.1/M tokens$0.1/M tokens
Output price$0.1/M tokens$0.4/M tokens
Context window128K tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJul 2025Feb 2026
At 10M a month$1.00$1.00$1.00$1.00
1M10M100M1B10M tokens

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

Where to run it1 host
GLM 4 32B

No hosts listed on OpenRouter.

Qwen3.5 Flash1 host
HostInOutContextUptime
  • Alibaba Cloud$0.07 in·$0.26 out·1M·100% up

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

Common questions

What is the difference between GLM 4 32B and Qwen3.5 Flash?

GLM 4 32B is developed by Zhipu AI while Qwen3.5 Flash is developed by Qwen. GLM 4 32B has a 128K token context window vs Qwen3.5 Flash's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GLM 4 32B or Qwen3.5 Flash?

It depends on your use case. GLM 4 32B and Qwen3.5 Flash 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 4 32B cost compared to Qwen3.5 Flash?

GLM 4 32B costs $0.1/M input tokens and Qwen3.5 Flash costs $0.1/M input tokens. Qwen3.5 Flash is $0.00/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 32B and Qwen3.5 Flash on Rival?

This page shows a side-by-side comparison of GLM 4 32B and Qwen3.5 Flash 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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