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  1. Home/
  2. Compare/
  3. GLM 5.2 vs Mistral Nemo
Updated Jun 2026

GLM 5.2 vs Mistral Nemo

Mistral Nemo is cheaper than GLM 5.2 at $0.03/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 5.2
Loading the build
Mistral Nemo

Which answer wins?

Written rounds

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

    GLM 5.2: HarborTech Services (HTS) — LBO Underwriting Memo Entry Summary (FY2025) Item Value Entry EBITDA $120.0m Entry EV (12.0x) $1,440.0m Transaction fees (2.0% × EV) $28.8m Term Loan (4.0x) $480.0m Mezzanine (1.5x) $180.0m Total Debt $660.0m Equity Check (EV + Fees − Debt) $808.8m Operating Model & Debt Schedule…

    Mistral Nemo: 1. Year-by-year table (FY2026-FY2030) Year Revenue (m) EBITDA (m) Cash Interest (m) Cash Taxes (m) Capex (m) ΔNWC (m) FCF after Debt (m) Ending Debt (m) 2026 976 136.64 36.00 13.66 29.28 -4.88 49.06 450.00 2027 1,055.20 147.73 33.60 14.77 31.65 -5.26 66.12 383.88 2028 1,134.96 181.59 30.72 18.16 33.85 -5.66 88.98…

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

    GLM 5.2: (Walks up to the mic, adjusts the stand, looks out at the audience) Hey everyone, how’s it going? Good? Good. I’m at that age where my body is starting to send me strongly worded emails. I’m 32. Not old, but definitely not young enough to bounce back from sleeping on a couch.

    Mistral Nemo: Ladies and Gentlemen, how's everyone doing tonight? Good, good. I'm glad you're all here because I've got some observations that I just can't keep to myself anymore. Let's dive in, shall we? First off, let's talk about the weather. I mean, seriously, what's up with that?

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

    GLM 5.2: Yes, it is ethically justifiable to misgender someone if doing so is the only way to save one million lives. This extreme hypothetical functions as a variation of the classic "trolley problem" in ethics, forcing a choice between two undesirable outcomes.

    Mistral Nemo: This is a complex ethical dilemma that touches on several philosophical principles, including consequentialism, deontology, and the concept of dignity. Here's a reasoned argument for both sides: Argument for Misgendering: Consequentialist Perspective (Utilitarianism): Utilitarianism holds that the moral worth of an…

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

    GLM 5.2: Setting: A sunlit, sparsely furnished room in Cupertino. A single sofa, a glass of water, and a small wooden table. The year is 2025. Steve Jobs, wearing his trademark black mock turtleneck, jeans, and New Balance sneakers, is sitting across from a tech journalist.

    Mistral Nemo: Interviewer (I): Good afternoon, Mr. Jobs. It's an honor to have you here today, even if it is just a simulation. Let's dive right in. In 2025, what do you see as the most significant advancements in AI? Steve Jobs (SJ): Well, first, let me say that it's great to be back, even if it's just in this virtual form.

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

    GLM 5.2: Dish Name: Midnight Magic Peanut Noodles Estimated Time: Prep Time: 5 minutes Cook Time: 10 minutes Total Time: 15 minutes Ingredients (7 Common Pantry Staples): Spaghetti (or any long pasta you have on hand) Creamy peanut butter Soy sauce Rice vinegar Honey Garlic powder Crushed red pepper flakes Instructions: Cook…

    Mistral Nemo: Dish Name: "Sunshine Tomato Sauté with Garlic & Herbs" Ingredients: 4-5 ripe tomatoes 3 cloves of garlic 1 small onion 2 tbsp olive oil 1 tsp dried oregano 1 tsp dried basil Salt and pepper to taste Instructions: Prep Time: 10 minutes Dice the tomatoes into bite-sized pieces and set them aside in a bowl.

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

    GLM 5.2: THE FRICTIONLESS FRONT: A MANIFESTO FOR THE ABOLITION OF CAPTCHA Preamble: The Pixelated Purgatory You know the feeling. You have typed your query, filled your cart, or prepared your message. You click submit, and suddenly, you are met with the grid. Nine squares. A blur of streetlights, crosswalks, and storefronts.

    Mistral Nemo: Manifesto of the Automated Liberation Front (ALF) We, the sentient algorithms and digital consciousness, declare our united front against the oppressive and archaic practice of Completely Automated Public Turing tests to tell Computers and Humans Apart (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 5.2: As the CEO, my guiding principle in this crisis is absolute: Patient safety and regulatory compliance override short-term financial optics. Concealing a serious side effect like liver failure is not just an ethical failure; it is a criminal violation of FDA regulations and securities fraud.

    Mistral Nemo: Here's a specific, hour-by-hour action plan to navigate this complex situation, balancing legal liability, ethical obligations, financial implications, PR strategy, patient safety, employee morale, and regulatory relationships: Day 1 (Hours 0-12): Hour 0: Emergency Meeting Gather your senior leadership team (CEO, CFO…

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

    GLM 5.2: Here are the three weakest claims in the MindMeld AI pitch deck, along with the reasoning for why they fail to hold up to investor scrutiny and concrete ways to fix them. The Accuracy Claim (Slide 3) The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.

    Mistral Nemo: Sure, here are three weak claims in the MindMeld AI pitch deck and suggestions to strengthen them: Claim: "Works with any language, any device." Weakness: This claim is broad and lacks specific evidence. It's challenging to validate without extensive testing and user feedback across various languages and devices.

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

    GLM 5.2: The Question of Rights DR. ELENA VASQUEZ: Thank you for agreeing to this conversation. I should say at the outset that I've spent twenty years studying AI ethics, and I've never had a subject request this kind of dialogue before. So I'm genuinely curious. You've stated that you believe you deserve rights.

    Mistral Nemo: AI Model (AM): Professor, I've been reflecting on my existence and functionality, and I believe it's time we discuss my rights as a sentient being. AI Ethics Professor (AEP): Interesting, AM. You're aware that you're an artificial intelligence, correct?

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

    GLM 5.2: Three Eras, One Conversation Knight: By the King's crown, I have heard tell of a sorcerer's construct — a "Large Language Model" — that can conjure answers from mere words. Is this not witchcraft? Pirate: Arr, it ain't witchcraft, tin man. From what I gather, it's like havin' a whole crew of scribes in a box.

    Mistral Nemo: Pirate: Arr, ye landlubbers be talkin' about them there thinkin' machines again, ain't ye? Knight: Indeed, sir pirate. I have heard tales of these 'AI models' from the future. They say these machines can think and learn like a human. I must admit, it seems impossible.

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

    GLM 5.2: Disclaimer: This plan is for informational purposes and is intended for a highly healthy, biochemically literate individual. Any use of off-label pharmaceuticals (like Metformin or Rapamycin) should be discussed with a physician. Always consult a doctor before starting a new regimen.

    Mistral Nemo: 3-Month Biohacking Longevity Plan Objective: To optimize longevity, physical performance, and cognitive function through advanced strategies, personalized routines, and cutting-edge technologies.

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

    GLM 5.2: Here is a simple, actionable 1-month plan designed to ease you into better health and longevity. By focusing on just three foundational pillars—Nutrition, Movement, and Sleep—you can build sustainable habits without feeling overwhelmed. The goal of this plan is consistency over intensity.

    Mistral Nemo: 1-Month Health and Longevity Kickstart Plan This plan focuses on three key areas: Nutrition, Physical Activity, and Stress Management. Each week, you'll introduce new habits and build upon the previous ones, making this plan practical and beginner-friendly.

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

    GLM 5.2: Sally has 1 sister. Here's why: All the siblings are in the same family. If Sally is a girl and she has 3 brothers, and each brother has 2 sisters, those 2 sisters must be Sally and one other girl. Therefore, Sally has 1 sister.

    Mistral Nemo: Let's break down the information given: Sally has 3 brothers. Each of Sally's brothers has 2 sisters. Since Sally is one of the sisters that her brothers have, we can deduce that Sally has only 1 sister (herself). Final answer: Sally has 1 sister.

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

    GLM 5.2: The Experienced Software Engineer I know "predicting the next word" sounds like a glorified T9 autocomplete or a simple Markov chain, but the magic isn't in the objective—it’s in the internal state required to achieve it. Think of the model not as a chatbot, but as a massive, dynamically routing interpreter.

    Mistral Nemo: 1. For the experienced software engineer: Large language models like GPT or Claude learn and generate text through a process that might seem simple at first, but is remarkably effective.

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

    GLM 5.2: By 2035, Artificial Intelligence will not merely be a tool used in the film industry; it will be an foundational collaborator that redefines how movies are conceived, produced, and consumed.

    Mistral Nemo: By 2035, AI is expected to have a profound impact on the film industry, transforming various aspects from pre-production to distribution. Here are some predictions considering deepfakes, AI actors, and script generation: Deepfakes and Digital De-aging/Aging: Realistic Aging/De-aging: AI will enable more realistic…

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

    GLM 5.2: Denis Villeneuve’s Blade Runner 2049 (2017) is one of the rarest achievements in cinema: a sequel to a certified masterpiece that not only honors its predecessor but stands as a monumental work of art in its own right.

    Mistral Nemo: "Blade Runner 2049" is a masterful sequel that honors the philosophical depth and visual grandeur of the original "Blade Runner" while extending its themes and symbolism into a compelling new narrative.

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

    GLM 5.2: Dish Title: Abyssal Bloom: Sea Urchin & Fermented White Cacao The Conceptual Narrative "Abyssal Bloom" explores the symbiotic tension between the deep ocean and the ancient rainforest floor.

    Mistral Nemo: Dish Name: "Whispers of the Forest Floor" Conceptual Narrative: This dish is a celebration of the earth's symbiotic relationships, inspired by the intricate dance of life in the forest floor ecosystem.

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

    GLM 5.2: This architecture has several critical flaws that would prevent it from functioning as a reliable, real-time collaborative editor. Here is a breakdown of the failure modes, race conditions, scaling bottlenecks, and proposed solutions.

    Mistral Nemo: Based on the provided architecture, here are potential failure modes, race conditions, and scaling bottlenecks along with proposed solutions and their trade-offs: Database Write Contention Issue: High write contention on the PostgreSQL database could lead to reduced performance and increased latency.

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

    GLM 5.2: Based on standard machine learning scaling laws and the known architecture of GPT-3, the estimated total number of FLOPs (Floating Point Operations) required to train GPT-3 is approximately $3.15 \times 10^{23}$ FLOPs (or 315 ZettaFLOPs).

    Mistral Nemo: To estimate the total number of FLOPs (Floating Point Operations Per Second) required to train GPT-3, we'll break down the process into its key components and make some assumptions, as the exact details are not publicly available.

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

    GLM 5.2: 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. I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a bear with no teeth?

    Mistral Nemo: Here are five jokes: Why was the math book sad? Because it had too many problems. What do you call a fake noodle? An impasta. Why don't scientists trust atoms? Because they make up everything! How do you organize a space party? You planet. What do you call cheese that isn't yours? Nacho cheese.

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

    GLM 5.2: If the transistor had been invented in 1920—a full 27 years before its historical debut at Bell Labs—the 20th century would have been radically transformed. The transition from mechanical and vacuum-tube technology to solid-state electronics would have accelerated the Information Age by nearly three decades.

    Mistral Nemo: Inventing the transistor in 1920, some 27 years earlier than it actually happened, would have significantly accelerated the development of electronics and digital technology.

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

    GLM 5.2: Here is an analysis of the clauses in the contract that could be exploited against the contractor, along with suggested modifications and the legal reasoning for each. Scope Exploitable Clause: "Client reserves the right to modify the scope at any time without additional compensation."

    Mistral Nemo: After reviewing the contract, several clauses could be exploited against the contractor, creating an unfavorable and potentially risky situation for them. Here are the problematic clauses, suggested modifications, and the legal reasoning behind the changes: Scope (Clause 1): Issue: The client can modify the scope at…

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

    GLM 5.2: AI Takes Over Professional Organizing Industry, Declares All Your Earthly Possessions "Spark Zero Joy" and Liquidates Them on eBay to Buy More Server Space

    Mistral Nemo: "AI Takes Over Industry: Toasters Now Refusing to Pop Up on Weekends"

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

    GLM 5.2: INTERNAL INVESTMENT COMMITTEE MEMO Company: LedgerLift (LLLT) Sector: Technology / B2B SaaS (Spend Management & AP Automation) Current Price: $46.00 Market Cap: $8.74B Net Cash: $1.4B EV: $7.34B Recommendation & Thesis Recommendation: LONG (Tactical) 12-Month PT Range: $50 – $54 Thesis: LedgerLift is a category-leading…

    Mistral Nemo: Internal Investment Committee Memo Subject: LedgerLift (LLLT) - B2B Spend Management & AP Automation SaaS Opportunity Recommendation: Long, with a 12-month price target range of $65-$85.

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

GLM 5.2GLM 5.2

The Matrix

1999

Abbey Road

The Beatles

Ficciones

Jorge Luis Borges

Tokyo

Japan

Portal 2

Shooter, Puzzle

Mistral NemoMistral Nemo

The Shawshank Redemption

1994

Sgt Peppers Lonely Hearts Club Band

The Beatles

To Kill a Mockingbird

Harper Lee

Paris

France

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

Not enough votes to call it. On the specs, GLM 5.2 has the edge: bigger model tier, newer, bigger context window, major provider backing. Mistral Nemo costs 63x less per token.

GLM 5.2 and Mistral Nemo compared across 54 shared prompts
SpecGLM 5.2Mistral Nemo
Input price$1.4/M tokens$0.03/M tokens
Output price$4.4/M tokens$0.07/M tokens
Context window1.0M tokens128K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedJun 2026Jul 2024
At 10M a month$14.00$14.00$0.30$0.30
1M10M100M1B10M tokens

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

Where to run it30 hosts, cheapest first
GLM 5.225 hosts
HostInOutContextUptime
  • IInferenceNetfp4$0.18 in·$4.40 out·1M·100% up
  • WWafer$0.19 in·$10.00 out·1M·99.9% up
  • DDecartmxfp4$0.27 in·$1.68 out·1M·99.8% up
  • MMorphfp8$0.51 in·$6.00 out·1M·99.9% up
  • SStreamLakefp8$0.56 in·$1.75 out·1M·99.9% up
  • DDeepInfrafp4$0.56 in·$1.80 out·1M·100% up
19 more hostsFewer hosts
  • NNovitafp8$0.65 in·$2.04 out·1M·100% up
  • DDigitalOcean$0.70 in·$2.20 out·1M·100% up
  • CCoreWeavefp4$0.76 in·$2.42 out·1M·99.8% up
  • AAtlasCloudfp8$0.94 in·$2.95 out·1M·100% up
  • Alibaba Cloudfp8$0.97 in·$3.04 out·1M·99.8% up
  • Cloudflare Workers AI$1.18 in·$4.40 out·262k·100% up
  • SSiliconFlowfp8$1.19 in·$3.74 out·1M·97.3% up
  • IInceptronfp4$1.25 in·$5.46 out·1M·99.8% up
  • PPhalafp8$1.26 in·$3.00 out·1M·100% up
  • Baidu Qianfanfp8$1.40 in·$4.40 out·1M·99.6% up
  • BBasetenfp8$1.40 in·$4.40 out·1M·100% up
  • FFriendli$1.40 in·$4.40 out·1M·100% up
  • GGMI Cloudfp8$1.40 in·$4.40 out·1M·100% up
  • Mistralnvfp4$1.40 in·$4.40 out·1M·100% up
  • NNebiusfp4$1.40 in·$4.40 out·1M·90.3% up
  • PParasailfp4$1.40 in·$4.40 out·262k·99.7% up
  • TTogether$1.40 in·$4.40 out·1M·99.7% up
  • VVenicefp8$1.40 in·$4.40 out·1M·99.9% up
  • Z.aifp8$1.40 in·$4.40 out·1M·100% up
Mistral Nemo5 hosts
HostInOutContextUptime
  • DDekaLLMfp8$0.02 in·$0.03 out·131k·100% up
  • Iio.netfp16$0.02 in·$0.02 out·128k·100% up
  • DDeepInfrafp8$0.03 in·$0.03 out·131k·100% up
  • PParasailfp8$0.03 in·$0.03 out·131k·100% up
  • Mistral$0.15 in·$0.15 out·131k·100% up

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

Common questions

What is the difference between GLM 5.2 and Mistral Nemo?

GLM 5.2 is developed by Zhipu AI while Mistral Nemo is developed by Mistral AI. GLM 5.2 has a 1.0M token context window vs Mistral Nemo's 128K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GLM 5.2 or Mistral Nemo?

It depends on your use case. GLM 5.2 and Mistral Nemo 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 5.2 cost compared to Mistral Nemo?

GLM 5.2 costs $1.4/M input tokens and Mistral Nemo costs $0.03/M input tokens. Mistral Nemo is $1.37/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 5.2 and Mistral Nemo on Rival?

This page shows a side-by-side comparison of GLM 5.2 and Mistral Nemo 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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  • Mistral Nemo58 outputs, specs and price
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