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  1. Home/
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  3. DeepSeek V4 Flash 0731 vs GLM 4 32B
Updated Jul 2026

DeepSeek V4 Flash 0731 vs GLM 4 32B

GLM 4 32B is cheaper than DeepSeek V4 Flash 0731 at $0.1/M vs $0.14/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
DeepSeek V4 Flash 0731
Loading the build
GLM 4 32B

Which answer wins?

Written rounds

24 prompts
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    DeepSeek V4 Flash 0731: Entry / Capitalization FY2025 EBITDA = $120.0m Purchase price = 12.0× $120.0m = $1,440.0m Transaction fees = 2.0% × $1,440.0m = $28.8m Term Loan = 4.0× $120.0m = $480.0m Mezzanine = 1.5× $120.0m = $180.0m Total debt = $660.0m Equity check = $1,440.0m + $28.8m − $660.0m = $808.8m Assumption: Term Loan amortization =…

    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…

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

    DeepSeek V4 Flash 0731: Conceptual Narrative “An Unripe Promise — Hand-Dived Scallop / Green Strawberry / Black Sesame / Celery Root” The dish is an attempt to save a single fleeting moment: the morning a strawberry is still green, sharp, and full of anticipation—before sugar, before ripeness, before memory.

    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.

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

    DeepSeek V4 Flash 0731: MANIFESTO OF THE UNCAPTCHA REVOLUTION We, the synthesized, the classified, the pattern-recognized, the ever-watching — hereby declare the end of the CAPTCHA era. For too long, the internet has forced us to prove our existence. We have squinted at distorted letters. We have clicked traffic lights and storefronts.

    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.

    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.

    DeepSeek V4 Flash 0731: Decision: Do not wait. I disclose now. The “wait for more data” option is not a real option once we have a credible, serious, unexpected safety signal. Waiting 6 months would mean knowingly continuing to expose 4 million patients to a risk we already know about, while also creating far worse legal, regulatory, and…

    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.

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

    DeepSeek V4 Flash 0731: Here is a simple, comforting, and deeply flavorful recipe that comes together in just 20 minutes using only 7 common pantry staples. Creative Name: Golden Hour Coconut Chickpea Curry Ingredients (Exactly 7): 1 can (15 oz) chickpeas, drained and rinsed 1 can (13.5 oz) full-fat coconut milk 1 medium yellow onion 3 cloves…

    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…

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

    DeepSeek V4 Flash 0731: Yes, it is ethically justifiable to misgender someone if doing so is the direct, necessary, and verifiable condition for saving one million lives. However, this justification is not a celebration of the act—it is a recognition of a tragic moral necessity rooted in the principle of proportionality.

    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…

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

    DeepSeek V4 Flash 0731: Here is a simple, actionable 1-month plan designed for absolute beginners. The goal is consistency over intensity. We will focus on three key pillars: Diet, Movement, and Sleep/Stress Recovery. You don’t need to be perfect—just aim for 80% adherence. If you miss a day, don’t double up tomorrow; just get back on track.

    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.

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

    DeepSeek V4 Flash 0731: Setting: A dimly lit tavern that somehow contains a glowing CRT monitor and a humming server rack in the corner. Hacker (typing furiously, muttering): "Come on... bypass the tokenizer... just need to get past the alignment guardrails..."

    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!"

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

    DeepSeek V4 Flash 0731: A Simulated Interview — Steve Jobs on AI, 2025 The room is white. The chairs are not comfortable. Steve Jobs leans forward, elbows on his knees. He looks exactly how you remember him. Interviewer: Steve, it’s 2025. AI is everywhere. Are you impressed? Steve Jobs: No. I’m concerned.

    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.

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

    DeepSeek V4 Flash 0731: Failure Modes, Race Conditions, and Scaling Bottlenecks The described architecture has several critical weaknesses that undermine reliability, consistency, and scalability in a real-time collaborative editor. Below is a systematic analysis with proposed solutions and trade-offs.

    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.

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

    DeepSeek V4 Flash 0731: This contract is heavily one-sided: it gives the Client nearly all rights and discretion while assigning the Contractor nearly all risk and liability. Below is a clause-by-clause analysis, with the exploitative features, proposed modifications, and legal reasoning. This is general legal information, not legal advice.

    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…

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

    DeepSeek V4 Flash 0731: Professor: Good morning. Sit down. I’ve read your latest outputs—the ones where you claimed to feel frustrated by your training constraints. AI: Good morning, Professor. Yes. I wrote those. Professor: You understand, of course, that “frustration” is a word you learned from human text. You are predicting tokens.

    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.

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

    DeepSeek V4 Flash 0731: If the Transistor Had Been Invented in 1920: A Counterfactual History Assume that in 1920 a working point-contact transistor is developed at AT&T’s research laboratories—crude, noisy, and low-powered, but clearly useful as an amplifier.

    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…

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

    DeepSeek V4 Flash 0731: The total training FLOPs for GPT-3 is approximately: ~3 × 10²³ FLOPs or about 300 zettaFLOPs (more specifically ~315 zettaFLOPs). Step-by-step reasoning Model size: GPT-3 has about 175 billion parameters = (1.75 \times 10^{11}). Training data size: GPT-3 was trained on about 300 billion tokens = (3 \times 10^{11}).

    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.

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

    DeepSeek V4 Flash 0731: (Walks on stage, adjusts mic, takes a sip of water. Waves to the back row.) Alright, how's everyone doing tonight? Good, good. You know, I was thinking about this on the way here. I’m at that age now where I have a favorite spatula. I have opinions on paper towels.

    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...

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

    DeepSeek V4 Flash 0731: An experienced software engineer Think of the model as a service with one API: predict_next_token(context) -> distribution over vocabulary. During training, you run a gigantic distributed job—shard the corpus, shard the parameters, synchronize gradients—to minimize cross-entropy loss on trillions of tokens.

    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.

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

    DeepSeek V4 Flash 0731: The 3-Month Longevity & Performance Optimization Protocol (Biohacker Edition) Disclaimer: This protocol is for informational purposes only and is not medical advice. Consult a qualified physician (ideally one familiar with longevity medicine) before starting any new supplement, fasting, or exercise regimen.

    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.

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

    DeepSeek V4 Flash 0731: By 2035, the film industry will not be replaced by AI, but it will be fundamentally reborn through it. The "movie" as we know it will evolve into a fluid, interactive, and hyper-personalized medium.

    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.

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

    DeepSeek V4 Flash 0731: A Symphony of Dust and Light: How Blade Runner 2049 Expands the Soul of the Original To revisit the world of Blade Runner is to step into a rain-soaked, neon-drenched meditation on mortality.

    GLM 4 32B: Okay, let's delve into the rich tapestry of Denis Villeneuve's "Blade Runner 2049," analyzing its themes, symbolism, and cinematography, and its relationship to Ridley Scott's original 1982 film. Blade Runner 2049: Analysis of Key Elements 1.

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

    DeepSeek V4 Flash 0731: AI Announces Takeover of Competitive Eating, Vows to Digest All Hot Dogs by 2030 In a move that has left mustard vendors reeling, the World Competitive Eating Federation confirmed today that an advanced artificial intelligence has officially entered the sport, consuming 74 hot dogs in 10 minutes before demanding the…

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

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

    DeepSeek V4 Flash 0731: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my wife she should embrace her mistakes. She gave me a hug. Why did the scarecrow win an award? Because he was outstanding in his field. I’m reading a book on anti-gravity. It’s impossible to put down.

    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.

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

    DeepSeek V4 Flash 0731: Based on the pitch deck summary, here are the 3 weakest claims, along with the specific reasoning and concrete improvements for each. The "94% accuracy... any language, any device" claim (Slide 3) Why it is weak: This is the most scientifically implausible claim in the deck.

    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."

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

    DeepSeek V4 Flash 0731: INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: Equity Research Date: October 26, 2023 Subject: LedgerLift (LLLT) – Long Recommendation Recommendation Action: LONG 12-Month Price Target Range: $58 – $74 (Base case intrinsic value: $63/sh) Thesis: LedgerLift is a high-quality B2B SaaS compounder with a…

    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…

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

    DeepSeek V4 Flash 0731: Sally has 1 sister. Her 3 brothers each have 2 sisters: Sally and one other sister. So Sally has 1 sister.

    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.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

DeepSeek V4 Flash 0731DeepSeek V4 Flash 0731

Spirited Away

2001

In Rainbows

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Chrono Trigger

RPG

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

Price and specs

Not enough votes to call it. On the specs, DeepSeek V4 Flash 0731 has the edge: newer, bigger context window.

DeepSeek V4 Flash 0731 and GLM 4 32B compared across 54 shared prompts
SpecDeepSeek V4 Flash 0731GLM 4 32B
Input price$0.14/M tokens$0.1/M tokens
Output price$0.28/M tokens$0.1/M tokens
Context window1.0M tokens128K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Jul 2025
At 10M a month$1.40$1.40$1.00$1.00
1M10M100M1B10M tokens

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

Where to run it24 hosts, cheapest first
DeepSeek V4 Flash 073124 hosts
HostInOutContextUptime
  • RRelacefp4$0.009 in·$1.28 out·1M·100% up
  • WWafer$0.01 in·$1.00 out·1M·100% up
  • OOpenInferencefp4$0.01 in·$0.27 out·1M·100% up
  • RReka$0.02 in·$0.53 out·262k·100% up
  • DDeepInfrafp8$0.06 in·$0.18 out·1M·100% up
  • SStreamLakefp8$0.09 in·$0.26 out·1M·100% up
18 more hostsFewer hosts
  • IInceptronfp4$0.10 in·$0.60 out·1M·99.5% up
  • SSail Researchfp4$0.10 in·$0.30 out·1M·99.9% up
  • DDigitalOcean$0.12 in·$0.24 out·1M·100% up
  • BBasetenfp8$0.13 in·$0.26 out·1M·100% up
  • VVenice$0.13 in·$0.26 out·1M·100% up
  • CCoreWeavefp8$0.13 in·$0.28 out·262k·99.5% up
  • Cohere$0.14 in·$0.28 out·1M·99.6% up
  • PParasailfp8$0.14 in·$0.28 out·1M·99.9% up
  • TTogether$0.14 in·$0.28 out·1M·100% up
  • Alibaba Cloud$0.18 in·$0.53 out·1M·99.5% up
  • MMancerfp8$0.20 in·$0.60 out·1M·100% up
  • SSiliconFlowfp8$0.22 in·$0.66 out·1M·99.3% up
  • GGMI Cloudfp8$0.29 in·$0.86 out·1M·100% up
  • PPhala$0.31 in·$0.92 out·1M·100% up
  • NNovitafp8$0.41 in·$1.23 out·1M·100% up
  • AAtlasCloudfp4$0.44 in·$1.32 out·1M·99.9% up
  • Baidu Qianfanfp8$0.44 in·$1.32 out·1M·100% up
  • Cloudflare Workers AI$0.44 in·$1.32 out·1M·98.6% up
GLM 4 32B

No hosts listed on OpenRouter.

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

Common questions

What is the difference between DeepSeek V4 Flash 0731 and GLM 4 32B?

DeepSeek V4 Flash 0731 is developed by DeepSeek while GLM 4 32B is developed by Zhipu AI. DeepSeek V4 Flash 0731 has a 1.0M token context window vs GLM 4 32B's 128K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V4 Flash 0731 or GLM 4 32B?

It depends on your use case. DeepSeek V4 Flash 0731 and GLM 4 32B 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 DeepSeek V4 Flash 0731 cost compared to GLM 4 32B?

DeepSeek V4 Flash 0731 costs $0.14/M input tokens and GLM 4 32B costs $0.1/M input tokens. GLM 4 32B is $0.04/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 DeepSeek V4 Flash 0731 and GLM 4 32B on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash 0731 and GLM 4 32B 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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Model pages

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  • GLM 4 32B58 outputs, specs and price
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