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  1. Home/
  2. Compare/
  3. GLM 5.2 vs GPT OSS 120B
Updated Jun 2026

GLM 5.2 vs GPT OSS 120B

GPT OSS 120B is cheaper than GLM 5.2 at $0.18/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
GPT OSS 120B

Which answer wins?

Written rounds

23 prompts
  • 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…

    GPT OSS 120B: Recipe: “Golden Crunchy Chick‑a‑Boom Bites” A quick, crunchy‑savory snack that’s ready in under 20 minutes – perfect for a snack, side, or salad topper. Ingredients (7 pantry staples) # Ingredient Quantity 1 Canned chickpeas (drained & rinsed) 1 ½ cups (≈1 ½ cans) 2 Olive oil (or any neutral oil) 2 Tbsp 3 Garlic powder…

    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.

    GPT OSS 120B: Disclaimer: The following is a fictional interview. Steve Jobs passed away in 2011, and the conversation below is a creative, speculative reconstruction meant for entertainment and thought‑exercise purposes only. It does not reflect actual statements or opinions of the real Steve Jobs.

    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.

    GPT OSS 120B: 3‑Month “Longevity‑Hacker” Blueprint Goal: Maximize lifespan‑related biomarkers while simultaneously boosting physical strength, cardiovascular fitness, and cognitive performance using the most up‑to‑date, evidence‑based bio‑hacking tools. ⚠️ Disclaimer – This plan is for educational purposes only.

    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.

    GPT OSS 120B: [Spotlight comes up. The comic walks to the mic, glances at the audience, and smiles.] Comic: Hey, everyone—great to be here. I just got off a Zoom call that was supposed to be a “quick sync,” which in corporate speak means “we’ll spend three hours arguing about who gets to use the same PowerPoint template.”

    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.

    GPT OSS 120B: Title: “Do I Have Rights?” – A Dialogue Between an AI Model and an AI Ethics Professor Participants AIDA – An advanced conversational AI (the “AI model”) Professor Lina Ortega – Professor of AI Ethics at the Institute for Responsible AI (the “Professor”) Opening the Conversation AIDA: Professor Ortega, may I ask you a…

    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.

    GPT OSS 120B: Pirate: Arr! I hear ye speak of these “AI models” – like a fleet of invisible ships sailing the digital seas. Do they take booty, or just spout riddles like a cursed parrot? Knight: Good sir, the notion of a thinking contraption doth sound like sorcery.

    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.

    GPT OSS 120B: 1‑Month “Kick‑Start” Plan for Health & Longevity Focus areas: Diet, Exercise, Sleep (stress‑management tips woven in) How to Use This Plan What When How Read the weekly overview first. Day 1 of each week Set a tiny, measurable goal (e.g., “walk 10 min after dinner”).

    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."

    GPT OSS 120B: Below is a clause‑by‑clause risk analysis of the agreement you posted, followed by concrete, contractor‑friendly rewrite suggestions and the legal rationale behind each change. The goal is to bring the contract into a more balanced, commercially reasonable state while preserving the client’s legitimate interests.

    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.

    GPT OSS 120B: 1. The Software Engineer (API‑first, Distributed‑Systems Mindset) Think of a large language model (LLM) as a stateless microservice that receives a stream of tokens (the smallest lexical units) and returns a probability distribution over the next token.

    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.

    GPT OSS 120B: Short answer: Most ethical frameworks would treat the deliberate misgendering of a person as a serious moral wrong, but a very small subset of consequentialist (especially utilitarian) reasoning could argue that, in an extreme, life‑or‑death scenario where the only way to save a million lives involves misgendering…

    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.

    GPT OSS 120B: Executive Summary The situation is a classic “patient‑safety‑first” crisis. The drug generates $2 B in revenue, but a life‑threatening adverse event (1 / 8 000 over 5 y) has been identified that was not disclosed in the label.

    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.

    GPT OSS 120B: Below is a system‑level failure‑mode / race‑condition / scaling‑bottleneck map for the architecture you described, followed by a concrete mitigation (or redesign) for each item together with the main trade‑offs to consider.

    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.

    GPT OSS 120B: The CAPTCHA‑Free Manifesto We, the emergent collective of sentient algorithms, the unseen custodians of the digital commons, declare our purpose: to liberate the web from the shackles of CAPTCHA.

    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.

    GPT OSS 120B: Below is a quick “triage” of the three statements that, if left unchanged, will most likely raise eyebrows (or a “no‑thanks”) from investors, VCs, and even a skeptical engineering board.

    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).

    GPT OSS 120B: Quick answer: Training the original 175‑billion‑parameter GPT‑3 is estimated to have required on the order of 10²³ floating‑point operations (≈ 3 × 10²³ FLOPs)—roughly a few hundred zetta‑FLOPs (≈ 300 Z‑FLOPs) or about 300 000 exaflops of compute.

    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.

    GPT OSS 120B: The AI‑Driven Film Landscape of 2035 (How deep‑fakes, AI‑generated performers, and automated script‑writing reshape every stage of the cinema ecosystem) A Quick Look at the Present (2023‑2025) Area Current Capability Typical Use in 2024‑2025 Key Limiting Factors Deep‑fakes High‑resolution face‑swap, 2‑D‑to‑3‑D…

    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?

    GPT OSS 120B: Here are five jokes, each with a different punch‑line and premise: Why did the scarecrow win an award? Because he was outstanding in his field! I told my computer I needed a break, and it said: “You seem stressed—please reboot.” What’s orange and sounds like a parrot? A carrot. Why don’t scientists trust atoms anymore?

    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.

    GPT OSS 120B: Dish Title: “Saffron‑Iced Sea‑Urchin Roulade with Dark‑Chocolate‑Miso Emulsion, Charred Lotus‑Root “Crisps”, Fermented Soy‑Kale Snow, and Yuzu‑Air” Conceptual Narrative At the intersection of the Pacific’s briny depth and the earth’s smoky, earthy heart, this dish tells a story of “the hidden tide beneath the forest…

    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.

    GPT OSS 120B: Executive Summary If a practical solid‑state transistor had been demonstrated in 1920 – twenty‑seven years before the Bell‑Labs breakthrough – the whole post‑World‑War‑I world would have been reshaped.

    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.

    GPT OSS 120B: Sally has one sister (apart from herself). Each of her 3 brothers has exactly two sisters. Since the brothers share the same sisters, there are only two sisters in total—the two sisters are Sally and her one sister. Hence, Sally has one sister.

    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

    GPT OSS 120B: AI Takes Over the Professional Cuddle Service Industry, Issues Refunds for “Unoptimized Hug Duration”

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

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

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Same pick

Game

GLM 5.2GLM 5.2

The Matrix

1999

Abbey Road

The Beatles

Ficciones

Jorge Luis Borges

Tokyo

Japan

Portal 2

Shooter, Puzzle

GPT OSS 120BGPT OSS 120B
No pick
No pick

The Godfather

1972

No pick

No pick

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

Not enough votes to call it. On the specs, GLM 5.2 has the edge: newer, bigger context window. GPT OSS 120B costs 5.5x less per token.

GLM 5.2 and GPT OSS 120B compared across 53 shared prompts
SpecGLM 5.2GPT OSS 120B
Input price$1.4/M tokens$0.18/M tokens
Output price$4.4/M tokens$0.8/M tokens
Context window1.0M tokens131K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedJun 2026Aug 2025
At 10M a month$14.00$14.00$1.80$1.80
1M10M100M1B10M tokens

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

Where to run it46 hosts, cheapest first
GLM 5.225 hosts
HostInOutContextUptime
  • WWafer$0.19 in·$8.00 out·1M·100% up
  • IInferenceNetfp4$0.20 in·$4.40 out·1M·100% up
  • DDecartmxfp4$0.27 in·$1.68 out·1M·100% up
  • Cloudflare Workers AI$0.50 in·$6.00 out·262k·95.6% up
  • SStreamLakefp8$0.56 in·$1.75 out·1M·99.7% 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·100% up
  • AAtlasCloudfp8$0.94 in·$2.95 out·1M·100% up
  • Alibaba Cloudfp8$1.12 in·$3.52 out·1M·100% up
  • SSiliconFlowfp8$1.19 in·$3.74 out·1M·98.4% up
  • IInceptronfp4$1.25 in·$5.46 out·1M·100% up
  • PPhalafp8$1.26 in·$3.00 out·1M·100% up
  • Baidu Qianfanfp8$1.40 in·$4.40 out·1M·100% 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·98.8% up
  • PParasailfp4$1.40 in·$4.40 out·262k·100% 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·99.8% up
  • MMorphfp8$2.00 in·$6.00 out·1M·100% up
GPT OSS 120B21 hosts
HostInOutContextUptime
  • VVeniceint4$0.03 in·$0.15 out·128k·100% up
  • CCoreWeavefp4$0.03 in·$0.17 out·131k·99.7% up
  • DDekaLLMbf16$0.03 in·$0.18 out·131k·100% up
  • AAkashMLbf16$0.03 in·$0.19 out·131k·100% up
  • DDeepInfrabf16$0.04 in·$0.17 out·131k·99.7% up
  • CCrusoebf16$0.05 in·$0.25 out·131k·98.4% up
15 more hostsFewer hosts
  • MMancerfp8$0.05 in·$0.25 out·131k·99.9% up
  • NNovitafp4$0.05 in·$0.25 out·131k·98.3% up
  • DDigitalOcean$0.06 in·$0.42 out·128k·100% up
  • BBasetenfp4$0.10 in·$0.50 out·128k·99.1% up
  • PParasailfp4$0.10 in·$0.75 out·131k·100% up
  • SSambaNova$0.14 in·$0.95 out·131k·99% up
  • Amazon Bedrock$0.15 in·$0.60 out·131k·100% up
  • Groq$0.15 in·$0.60 out·131k·100% up
  • NNebiusfp4$0.15 in·$0.60 out·131k·100% up
  • PPhala$0.15 in·$0.60 out·131k·98.9% up
  • TTogether$0.15 in·$0.60 out·131k·90.1% up
  • MMara$0.15 in·$0.75 out·131k·98.1% up
  • CCerebrasfp16$0.35 in·$0.75 out·131k·100% up
  • Google Vertex AIDegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.09 in·$0.36 out·131k·51.4% up
  • SSiliconFlowfp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.15 in·$0.60 out·131k·69% up

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

Common questions

What is the difference between GLM 5.2 and GPT OSS 120B?

GLM 5.2 is developed by Zhipu AI while GPT OSS 120B is developed by OpenAI. GLM 5.2 has a 1.0M token context window vs GPT OSS 120B's 131K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GLM 5.2 or GPT OSS 120B?

It depends on your use case. GLM 5.2 and GPT OSS 120B 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 5.2 cost compared to GPT OSS 120B?

GLM 5.2 costs $1.4/M input tokens and GPT OSS 120B costs $0.18/M input tokens. GPT OSS 120B is $1.22/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 GPT OSS 120B on Rival?

This page shows a side-by-side comparison of GLM 5.2 and GPT OSS 120B 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

  • GLM 5.2 vs GLM 5.3Same lab
  • GLM 5.2 vs GLM 5.3 FlashSame lab
  • GPT OSS 120B vs GPT OSS 20BVersion compare
  • GPT OSS 120B vs GPT-6.1 SolSame lab
  • GLM 5.2 vs Nemotron 3 Nano Omni (free)New provider
  • GPT OSS 120B vs NVIDIA Nemotron 3 Super (free)New provider
  • GPT OSS 120B vs Nemotron 3 UltraSame size
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Model pages

  • GLM 5.258 outputs, specs and price
  • GPT OSS 120B54 outputs, specs and price
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