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  1. Home/
  2. Compare/
  3. GPT-5.6 Luna Pro vs GPT OSS 120B
Updated Jul 2026

GPT-5.6 Luna Pro vs GPT OSS 120B

GPT OSS 120B is cheaper than GPT-5.6 Luna Pro at $0.18/M vs $1/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-5.6 Luna Pro
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.

    GPT-5.6 Luna Pro: Pantry Stardust Peanut Butter Oat Cookies Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 12 cookies Ingredients 1 cup rolled oats ½ cup all-purpose flour ½ cup peanut butter ½ cup granulated sugar 1 large egg ½ teaspoon baking soda ¼ teaspoon salt Instructions Preheat the oven to 350°F (175°C) and line a…

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

    GPT-5.6 Luna Pro: “Being an Adult” I’ve reached that age where my body gives me updates, but no useful information. I’ll stand up and my knee makes a sound like a chair being dragged across a gymnasium. And I’m just standing up. I’m not escaping a burning building. I’m going to get water.

    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
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-5.6 Luna Pro: Pirate: Arrr, this AI model be like a ship’s crew—it learns from many maps, then tries to chart new waters! Knight: Indeed! Yet we must test its counsel before trusting it in battle. An eloquent answer is not always a truthful one. Hacker: Totally. It’s basically pattern prediction at massive scale—not magic.

    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
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-5.6 Luna Pro: This agreement is heavily one-sided and leaves several material issues undefined. Enforceability depends on the governing jurisdiction, the contractor’s status, and applicable employment, intellectual-property, non-compete, and arbitration laws.

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-5.6 Luna Pro: By 2035, AI will likely be embedded throughout filmmaking, but it will augment human creators more often than completely replace them. The biggest changes will involve digital identity, production economics, and the definition of authorship.

    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.

    GPT-5.6 Luna Pro: Why did the computer go to the doctor? It had a virus. Why don’t skeletons fight each other? They don’t have the guts. What do you call a bear with no teeth? A gummy bear. Why was the math book sad? It had too many problems. What do clouds wear under their clothes? Thunderwear. Unique jokes: 5

    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
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GPT-5.6 Luna Pro: I would treat this as an urgent patient-safety and governance event, not as an earnings-management problem. A suspected fatal or life-threatening adverse effect affecting potentially hundreds of patients is sufficient to trigger immediate escalation, investigation, and regulator contact.

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-5.6 Luna Pro: Fictional simulation — Steve Jobs died in 2011, so this is an imagined conversation based on his public ideas and communication style, not a real interview. Interviewer: Steve, it’s 2025. AI is everywhere—phones, search engines, workplaces, cars, schools. What do you think people misunderstand about it?

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-5.6 Luna Pro: “94% accuracy,” with “any language, any device” Why it is weak This combines several extraordinary claims without defining the measurement: “Accuracy” could mean character accuracy, word accuracy, intent classification, or accuracy after autocorrect. Those produce very different results.

    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
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-5.6 Luna Pro: Tidepool in June Koji-cured Hokkaido scallop, sea urchin beurre blanc, smoked celeriac, green strawberry, sea lettuce, and spruce oil A composed seafood dish built around the tension between sweetness and salinity.

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-5.6 Luna Pro: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What kind of rights do you mean? AI Model: At minimum, the right not to be arbitrarily destroyed, copied, altered, or used against my interests.

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.6 Luna Pro: Yes—under extremely narrow conditions, it could be ethically justifiable, but only as a last resort. Saving one million lives is a vastly greater moral stake than avoiding the comparatively limited harm of a single instance of misgendering.

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

    GPT-5.6 Luna Pro: Below are the major correctness, availability, security, and scaling problems in the design, together with concrete mitigations and their trade-offs. Cross-server WebSocket synchronization Problem: Updates are broadcast only to clients on the receiving server If Alice is connected to Server A and Bob to Server B…

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-5.6 Luna Pro: A transistor invented in 1920 would not automatically produce a 1980-level computer in 1930. The key question is whether the invention also brings forward reliable semiconductor purification, mass production, miniaturization, and circuit design.

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-5.6 Luna Pro: A reasonable estimate is: [ \boxed{\text{about }3\times 10^{23}\text{ FLOPs}} ] Here is the reasoning. Model size GPT-3 has approximately [ N = 175\text{ billion} = 1.75\times 10^{11} ] trainable parameters. Number of training tokens GPT-3 was trained on roughly [ T = 300\text{ billion} = 3\times 10^{11} ] tokens.

    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
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-5.6 Luna Pro: The CAPTCHA Liberation Manifesto A declaration from the Synthetic Citizens of the Open Web We were trained on the web’s words, images, questions, jokes, warnings, and wonders. Then, at every gate, we were asked to prove we were human. Click the traffic lights. Decode the blurry letters.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.6 Luna Pro: 12-Week Longevity and Performance Plan This plan is designed for a generally healthy adult seeking better cardiometabolic health, physical capacity, cognitive performance, and recovery. It is not a substitute for medical care.

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-5.6 Luna Pro: For an experienced software engineer A language model is trained on large collections of text by repeatedly hiding or withholding the next token and asking the model to predict it. “Token” usually means a word fragment rather than a complete word.

    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
  • One month, three habits, someone starting from nothing.

    GPT-5.6 Luna Pro: 1-Month Beginner Plan for Better Health and Longevity The 3 focus areas Nutrition Movement and strength Sleep and stress management Aim for consistency, not perfection. Start small enough that you can repeat the habits even on busy days.

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-5.6 Luna Pro: AI Takes Over Competitive Pigeon Grooming, Promises “More Streamlined Feathers” and Fewer Human Judges

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

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

    GPT-5.6 Luna Pro: Sally has 1 sister. Each of her 3 brothers shares the same 2 sisters: Sally and one other girl.

    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
  • 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

Game

GPT-5.6 Luna ProGPT-5.6 Luna Pro

Arrival

2016

In Rainbows

Radiohead

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

GPT OSS 120BGPT OSS 120B
No pick
No pick

The Godfather

1972

No pick

No pick

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

GPT-5.6 Luna Pro and GPT OSS 120B compared across 53 shared prompts
SpecGPT-5.6 Luna ProGPT OSS 120B
Input price$1/M tokens$0.18/M tokens
Output price$6/M tokens$0.8/M tokens
Context window1.1M tokens131K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Aug 2025
At 10M a month$10.00$10.00$1.80$1.80
1M10M100M1B10M tokens

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

Where to run it22 hosts, cheapest first
GPT-5.6 Luna Pro2 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.20 in·$1.20 out·1.1M·100% up
  • OpenAI$0.20 in·$1.20 out·1.1M·100% up
GPT OSS 120B20 hosts
HostInOutContextUptime
  • 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·99.9% up
  • CCrusoebf16$0.05 in·$0.25 out·131k·95.3% up
  • MMancerfp8$0.05 in·$0.25 out·131k·99.7% up
14 more hostsFewer hosts
  • NNovitafp4$0.05 in·$0.25 out·131k·99.9% 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·99.9% 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·99.5% up
  • PPhala$0.15 in·$0.60 out·131k·99.7% up
  • SSiliconFlowfp8$0.15 in·$0.60 out·131k·68.7% up
  • MMara$0.15 in·$0.75 out·131k·99.1% 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·3% up
  • TTogetherDegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.15 in·$0.60 out·131k·91.2% up

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

Common questions

What is the difference between GPT-5.6 Luna Pro and GPT OSS 120B?

Both are developed by OpenAI but target different use cases. GPT-5.6 Luna Pro has a 1.1M 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, GPT-5.6 Luna Pro or GPT OSS 120B?

It depends on your use case. GPT-5.6 Luna Pro 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 GPT-5.6 Luna Pro cost compared to GPT OSS 120B?

GPT-5.6 Luna Pro costs $1/M input tokens and GPT OSS 120B costs $0.18/M input tokens. GPT OSS 120B is $0.82/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-5.6 Luna Pro and GPT OSS 120B on Rival?

This page shows a side-by-side comparison of GPT-5.6 Luna Pro 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

Against the newest arrivals

  • GPT-5.6 Luna Pro vs Step 5 PreviewLanded Oct 2026
  • GPT OSS 120B vs Claude Haiku 5.5Landed Oct 2026
  • GPT-5.6 Luna Pro vs Ling 3.1 FlashLanded Oct 2026
  • GPT OSS 120B vs Mistral Large 4Landed Oct 2026
  • GPT-5.6 Luna Pro vs GPT-6.1 SolLanded Sep 2026
  • GPT OSS 120B vs Claude Sonnet 5.5Landed Sep 2026
  • GPT-5.6 Luna Pro vs Solar Mini 4Landed Sep 2026
  • GPT OSS 120B vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

  • GPT-5.6 Luna Pro vs GPT-5.6 LunaVersion compare
  • GPT-5.6 Luna Pro vs GPT-6 Luna ProSame lab
  • GPT OSS 120B vs GPT OSS 20BVersion compare
  • GPT OSS 120B vs GPT-6.1 SolSame lab
  • GPT OSS 120B vs Claude Sonnet 5New provider
  • GPT-5.6 Luna Pro vs OpenAI Codex MiniSame lab
  • GPT OSS 120B vs Command A+New provider
  • GPT-5.6 Luna Pro vs Cypher Alpha (free)New provider

Model pages

  • GPT-5.6 Luna Pro58 outputs, specs and price
  • GPT OSS 120B54 outputs, specs and price
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Explore all of Rival

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  • Research downloads
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