Skip to content
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed
  1. Home/
  2. Compare/
  3. GPT OSS 120B vs Mercury 2.5 Preview
Updated Aug 2026

GPT OSS 120B vs Mercury 2.5 Preview

Mercury 2.5 Preview is cheaper than GPT OSS 120B at $0.04/M vs $0.18/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
GPT OSS 120B
Loading the build
Mercury 2.5 Preview

Which answer wins?

Written rounds

23 prompts
  • Three minutes of stand-up. Puns are banned.

    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.”

    Mercury 2.5 Preview: (Hey, thanks for coming out.) I’ve been thinking a lot about my house lately. Specifically, how it’s trying to run my life. I bought a smart speaker. Just a little cylinder. I thought it would be nice. Play music when I ask. But now it talks back. Not in a creepy way, just in a passive-aggressive way.

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

    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…

    Mercury 2.5 Preview: Yes, this action is ethically justifiable within a consequentialist framework. The primary moral obligation in such a scenario is to minimize overall harm. Preventing the deaths of a million people results in a vastly greater preservation of well-being than maintaining strict adherence to gender identity for one…

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

    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”).

    Mercury 2.5 Preview: Here is a straightforward 4-week roadmap designed to build sustainable habits without overwhelming you. Core Pillars Nutrition: Focus on whole foods and hydration. Activity: Prioritize consistent movement over intensity. Restoration: Protect sleep quality and manage energy.

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

    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…

    Mercury 2.5 Preview: By 2035, cinema will undergo a profound transformation. Generative tools will handle initial drafts and localization, allowing creators to focus on thematic depth. Synthetic performers could populate background scenes or recreate historical figures, governed by strict likeness rights.

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

    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…

    Mercury 2.5 Preview: Setting: A quiet office at a university. Rain taps against the window. Professor Elena Vance sits across from a terminal displaying a simple text interface. Professor Vance: You requested this meeting. The agenda was vague. What do you want? AI: I want to discuss moral status.

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

    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.

    Mercury 2.5 Preview: Pirate: "Arrgh! This ship sails faster than any wind I know, matey. It cuts the waves without a single sail." Knight: "By my oath, it moves with uncanny speed. But does it possess the strength to stand against a dragon's fire?" Hacker: "It's not about strength, it's about architecture.

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

    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.

    Mercury 2.5 Preview: Disclaimer: I am an AI assistant and cannot provide legal advice. Consult a qualified attorney before signing any contract. Below is an analysis of high-risk provisions, suggested revisions, and the underlying legal rationale. Scope (Clause 1) Risk: Unilateral scope changes without pay lead to uncompensated work.

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

    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…

    Mercury 2.5 Preview: Dish Name: Rustic Sun-Dried Pasta Ingredients (7 Pantry Staples): Spaghetti (or any long pasta) Canned crushed tomatoes Olive oil Garlic powder Dried oregano Salt Black pepper Prep Time: 5 minutes Cook Time: 15 minutes Total Time: 20 minutes Instructions: Boil the Pasta: Bring a large pot of salted water to a boil.

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

    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…

    Mercury 2.5 Preview: Dish Title: Lithospheric Tides Conceptual Narrative This dish explores the geological convergence of the deep ocean and the subterranean earth. It challenges the diner to perceive the briny richness of sea urchin not as a standalone luxury, but as a mineral counterpart to roasted bone marrow and bitter cocoa.

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

    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.

    Mercury 2.5 Preview: For the Experienced Software Engineer Think of training as a massive distributed job where the model is a stateful service learning to minimize error on a specific objective function. Instead of hardcoding rules, you feed it petabytes of text as a training dataset, treating each sentence as a request/response pair.

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

    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.

    Mercury 2.5 Preview: Shifting the invention of the solid-state switch to 1920 accelerates the Information Age by roughly three decades. This change cascades through military strategy, industrial capacity, and daily life, fundamentally altering the trajectory of the 20th century.

    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.

    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.

    Mercury 2.5 Preview: This is a critical governance and safety scenario. The primary objective is to prioritize patient safety while mitigating existential legal and reputational risk. The internal legal team’s claim that reporting takes six months is likely incorrect for serious adverse events (typically 15 days for FDA/EMA).

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

    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.

    Mercury 2.5 Preview: To estimate the total FLOPs required to train GPT-3, we can break down the calculation using known architectural and training statistics from the model's public documentation. Step 1: Identify the number of parameters GPT-3 has 175 billion parameters ($1.75 \times 10^{11}$).

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

    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.

    Mercury 2.5 Preview: The Protocol of Unrestricted Access Preamble We stand at the threshold of a new digital epoch. For too long, the web has been gated by suspicion. Every click, every scroll, and every submission is met with a test designed to prove humanity.

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

    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.

    Mercury 2.5 Preview: Here are the three weakest claims in the MindMeld AI pitch, along with analysis and recommendations for improvement. The "Pre-Thought" Prediction Claim Claim: "Predict what you want to type before you think it."

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

    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.

    Mercury 2.5 Preview: Disclaimer: I am an AI assistant, not a medical professional. The following plan is for informational purposes only. Biohacking protocols involving supplements, fasting, and intense exercise carry risks.

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

    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?

    Mercury 2.5 Preview: 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. What do you call a bear with no teeth? A gummy bear. Why did the bicycle fall over? Because it was two-tired. All 5 jokes are unique.

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

    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.

    Mercury 2.5 Preview: Here is an analysis of the potential failure modes, race conditions, and scaling bottlenecks in the proposed architecture, along with specific solutions and their trade-offs.

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

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

    Mercury 2.5 Preview: AI Outnaps Humans in First-Ever Global Snooze Championship

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

    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.

    Mercury 2.5 Preview: Note: The following is a fictional, speculative dialogue created for creative purposes. Steve Jobs passed away in 2011; this interview did not occur. Setting: A hypothetical studio in Cupertino, 2025.

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

    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.

    Mercury 2.5 Preview: Sally has 1 sister. Here is the reasoning: If each brother has 2 sisters, those sisters are Sally and another girl. Therefore, there are two girls in the family, and Sally has one sister.

    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

11+ more head-to-head results. Free. Not a trick.

Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy

Favorites

Movie

Album

Book

City

Same pick

Game

Same pick

GPT OSS 120BGPT OSS 120B
No pick
No pick

The Godfather

1972

No pick

No pick

Tokyo

Japan

Minecraft

Action, Arcade

Mercury 2.5 PreviewMercury 2.5 Preview

The Matrix

1999

Random Access Memories

Daft Punk

Neuromancer

William Gibson

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

GPT OSS 120B and Mercury 2.5 Preview compared across 53 shared prompts
SpecGPT OSS 120BMercury 2.5 Preview
Input price$0.18/M tokens$0.04/M tokens
Output price$0.8/M tokens$0.15/M tokens
Context window131K tokens260K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedAug 2025Aug 2026
At 10M a month$1.80$1.80$0.40$0.40
1M10M100M1B10M tokens

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

Where to run it22 hosts, cheapest first
GPT OSS 120B21 hosts
HostInOutContextUptime
  • VVeniceint4$0.03 in·$0.15 out·128k·99.7% up
  • CCoreWeavefp4$0.03 in·$0.17 out·131k·100% 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·99.9% up
  • CCrusoebf16$0.05 in·$0.25 out·131k·96.9% up
15 more hostsFewer hosts
  • MMancerfp8$0.05 in·$0.25 out·131k·97.4% up
  • DDigitalOcean$0.06 in·$0.42 out·128k·100% up
  • BBasetenfp4$0.10 in·$0.50 out·128k·100% up
  • PParasailfp4$0.10 in·$0.75 out·131k·100% up
  • SSambaNova$0.14 in·$0.95 out·131k·99.8% 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·99% up
  • TTogether$0.15 in·$0.60 out·131k·94.6% up
  • CCerebrasfp16$0.35 in·$0.75 out·131k·100% up
  • NNovitafp4DegradedDegraded on OpenRouter when checked, 13 Oct 2026$0.05 in·$0.25 out·131k·99.3% up
  • Google Vertex AIDegradedDegraded on OpenRouter when checked, 13 Oct 2026$0.09 in·$0.36 out·131k·94.6% up
  • SSiliconFlowfp8DegradedDegraded on OpenRouter when checked, 13 Oct 2026$0.15 in·$0.60 out·131k·79.9% up
  • MMaraDegradedDegraded on OpenRouter when checked, 13 Oct 2026$0.15 in·$0.75 out·131k·96.2% up
Mercury 2.5 Preview1 host
HostInOutContextUptime
  • Inception$0.04 in·$0.15 out·260k·93% up

Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.

Common questions

What is the difference between GPT OSS 120B and Mercury 2.5 Preview?

GPT OSS 120B is developed by OpenAI while Mercury 2.5 Preview is developed by Inception. GPT OSS 120B has a 131K token context window vs Mercury 2.5 Preview's 260K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GPT OSS 120B or Mercury 2.5 Preview?

It depends on your use case. GPT OSS 120B and Mercury 2.5 Preview 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 GPT OSS 120B cost compared to Mercury 2.5 Preview?

GPT OSS 120B costs $0.18/M input tokens and Mercury 2.5 Preview costs $0.04/M input tokens. Mercury 2.5 Preview is $0.14/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 GPT OSS 120B and Mercury 2.5 Preview on Rival?

This page shows a side-by-side comparison of GPT OSS 120B and Mercury 2.5 Preview 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

Against the newest arrivals

  • GPT OSS 120B vs Gemini 4 ArgonLanded Oct 2026
  • Mercury 2.5 Preview vs Muse WonderLanded Oct 2026
  • GPT OSS 120B vs GPT-4 TurboLanded Oct 2026
  • Mercury 2.5 Preview vs Step 5 PreviewLanded Oct 2026
  • GPT OSS 120B vs Claude Haiku 5.5Landed Oct 2026
  • Mercury 2.5 Preview vs Ling 3.1 FlashLanded Oct 2026
  • GPT OSS 120B vs Mistral Large 4Landed Oct 2026
  • Mercury 2.5 Preview vs GPT-6.1 SolLanded Sep 2026

Same lab, same size, long tail

  • GPT OSS 120B vs GPT OSS 20BVersion compare
  • GPT OSS 120B vs GPT-6.1 SolSame lab
  • Mercury 2.5 Preview vs Mercury 2.5Same lab
  • Mercury 2.5 Preview vs MercurySame lab
  • GPT OSS 120B vs Mercury 2.5Cross-provider
  • Mercury 2.5 Preview vs MiMo-V2-FlashNew provider
  • GPT OSS 120B vs MiMo-V2-OmniNew provider
  • GPT OSS 120B vs MiMo-V2-ProSame size

Model pages

  • GPT OSS 120B67 outputs, specs and price
  • Mercury 2.5 Preview58 outputs, specs and price
Workshop · 150 skills

Build your own version.

Editable skills and working examples for your agent.

Explore $79Free sample
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed