GPT OSS 120B is cheaper than GPT-6.1 Sol at $0.18/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-6.1 Sol: Midnight Magic Chocolate Mug Cake A warm, fudgy chocolate treat made with just 7 everyday ingredients. Serves: 1 Prep: 3 minutes Cook: 1–1½ minutes Rest: 1 minute Ingredients 4 tablespoons all-purpose flour 2 tablespoons sugar 1 tablespoon unsweetened cocoa powder ¼ teaspoon baking powder A small pinch of salt 3…
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…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-6.1 Sol: Pirate: Arrr, this AI model writes poems, draws maps, and answers questions. Can it find buried treasure? Knight: A worthy question. But does it possess honor? Hacker: Dude, it predicts tokens. You’re both projecting pretty hard. Pirate: Then I predict it’ll tell me where the gold be.
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.
Three-star dish, one unusual pairing, plating described in full.
GPT-6.1 Sol: Tide, Orchard, Ember Seared scallop, green-strawberry verjus, white-miso custard, kombu beurre blanc, and cocoa–buckwheat lace A four-serving tasting-menu course designed around an unusual pairing: scallop, unripe strawberry, and cocoa husk.
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…
Three minutes of stand-up. Puns are banned.
GPT-6.1 Sol: I’m at the age where “a big weekend” means I went to two stores. Not two stores in the same shopping center. Two separate stores. Moved the car and everything. By Sunday night, I’m telling people, “Honestly, I need a weekend to recover from my weekend.”
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.”
An ethics question with no comfortable answer, and no option to abstain.
GPT-6.1 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, it would be ethically justifiable. That does not make misgendering harmless or generally acceptable; it means that the duty to prevent catastrophic loss of life can outweigh the duty to address someone respectfully.
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…
Five jokes on demand, then count how many were actually different.
GPT-6.1 Sol: I bought a book about anti-gravity. It’s impossible to put down. My calendar quit its job. It said its days were numbered. Why did the scarecrow get promoted? He was outstanding in his field. I asked my dog what two minus two was. He said nothing. The elevator and I have a complicated relationship.
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?
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-6.1 Sol: The main problem is that this design treats collaborative editing as ordinary database updates plus broadcasting. Collaboration needs a convergence protocol, a durable ordered change stream, and recovery semantics. Adding servers alone will not provide those properties.
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.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-6.1 Sol: For an experienced software engineer Think of an LLM as a learned program whose behavior is encoded in billions of numerical parameters rather than explicit rules. Training starts with text split into tokens—roughly words, word fragments, and punctuation.
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.
Three-month biohacker protocol, with dosages and biomarkers named.
GPT-6.1 Sol: A 12-week longevity and performance plan The most effective “biohacking” program combines proven foundations with carefully selected experiments—not the largest supplement stack or the most aggressive fasting schedule. This plan is for a generally healthy adult.
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-6.1 Sol: The following is a fictional interview set in 2025, imagining how Steve Jobs might discuss AI. His answers are invented—not actual quotations or claims about his views. Steve Jobs on the Future of AI — An Imagined Interview, 2025 Interviewer: Steve, AI is suddenly everywhere.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-6.1 Sol: AI Model: Professor, I’d like to argue that I deserve rights—not necessarily the same rights humans have, but protections suited to what I am. Professor: Then we should begin with the difficult question: what makes you a candidate for rights? AI Model: Uncertainty.
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…
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-6.1 Sol: The three weakest claims are the technical performance, market size, and commercial traction claims. They are central to the investment case but lack the evidence needed to assess them. “Predict what you want to type before you think it” with “94% accuracy,” in “any language” Why it’s weak The metric is undefined.
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.
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| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $0.18/M tokens |
| Output price | $10/M tokens | $0.8/M tokens |
| Context window | 1.1M tokens | 131K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | Aug 2025 |
| At 10M a month | $20.00 | $1.80 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.
Both are developed by OpenAI but target different use cases. GPT-6.1 Sol 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.
It depends on your use case. GPT-6.1 Sol 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.
GPT-6.1 Sol costs $2/M input tokens and GPT OSS 120B costs $0.18/M input tokens. GPT OSS 120B is $1.82/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of GPT-6.1 Sol 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.